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Experimental Design - Independent, Dependent, and Controlled Variables

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Scientific experiments are meant to show cause and effect of a phenomena (relationships in nature).  The “ variables ” are any factor, trait, or condition that can be changed in the experiment and that can have an effect on the outcome of the experiment.

An experiment can have three kinds of variables: i ndependent, dependent, and controlled .

• The independent variable is one single factor that is changed by the scientist followed by observation to watch for changes. It is important that there is just one independent variable, so that results are not confusing.
• The dependent variable is the factor that changes as a result of the change to the independent variable.
• The controlled variables (or constant variables) are factors that the scientist wants to remain constant if the experiment is to show accurate results. To be able to measure results, each of the variables must be able to be measured.

For example, let’s design an experiment with two plants sitting in the sun side by side. The controlled variables (or constants) are that at the beginning of the experiment, the plants are the same size, get the same amount of sunlight, experience the same ambient temperature and are in the same amount and consistency of soil (the weight of the soil and container should be measured before the plants are added). The independent variable is that one plant is getting watered (1 cup of water) every day and one plant is getting watered (1 cup of water) once a week. The dependent variables are the changes in the two plants that the scientist observes over time.

Can you describe the dependent variable that may result from this experiment? After four weeks, the dependent variable may be that one plant is taller, heavier and more developed than the other. These results can be recorded and graphed by measuring and comparing both plants’ height, weight (removing the weight of the soil and container recorded beforehand) and a comparison of observable foliage.

Using What You Learned: Design another experiment using the two plants, but change the independent variable. Can you describe the dependent variable that may result from this new experiment?

Think of another simple experiment and name the independent, dependent, and controlled variables. Use the graphic organizer included in the PDF below to organize your experiment's variables.

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What Are Dependent, Independent & Controlled Variables?

What Is a Responding Variable in Science Projects?

Say you're in lab, and your teacher asks you to design an experiment. The experiment must test how plants grow in response to different colored light. How would you begin? What are you changing? What are you keeping the same? What are you measuring?

These parameters of what you would change and what you would keep the same are called variables. Take a look at how all of these parameters in an experiment are defined, as independent, dependent and controlled variables.

What Is a Variable?

A variable is any quantity that you are able to measure in some way. This could be temperature, height, age, etc. Basically, a variable is anything that contributes to the outcome or result of your experiment in any way.

In an experiment there are multiple kinds of variables: independent, dependent and controlled variables.

What Is an Independent Variable?

An independent variable is the variable the experimenter controls. Basically, it is the component you choose to change in an experiment. This variable is not dependent on any other variables.

For example, in the plant growth experiment, the independent variable is the light color. The light color is not affected by anything. You will choose different light colors like green, red, yellow, etc. You are not measuring the light.

What Is a Dependent Variable?

A dependent variable is the measurement that changes in response to what you changed in the experiment. This variable is dependent on other variables; hence the name! For example, in the plant growth experiment, the dependent variable would be plant growth.

You could measure this by measuring how much the plant grows every two days. You could also measure it by measuring the rate of photosynthesis. Either of these measurements are dependent upon the kind of light you give the plant.

What Are Controlled Variables?

A control variable in science is any other parameter affecting your experiment that you try to keep the same across all conditions.

For example, one control variable in the plant growth experiment could be temperature. You would not want to have one plant growing in green light with a temperature of 20°C while another plant grows in red light with a temperature of 27°C.

You want to measure only the effect of light, not temperature. For this reason you would want to keep the temperature the same across all of your plants. In other words, you would want to control the temperature.

Another example is the amount of water you give the plant. If one plant receives twice the amount of water as another plant, there would be no way for you to know that the reason those plants grew the way they did is due only to the light color their received.

The observed effect could also be due in part to the amount of water they got. A control variable in science experiments is what allows you to compare other things that may be contributing to a result because you have kept other important things the same across all of your subjects.

Graphing Your Experiment

When graphing the results of your experiment, it is important to remember which variable goes on which axis.

The independent variable is graphed on the x-axis . The dependent variable , which changes in response to the independent variable, is graphed on the y-axis . Controlled variables are usually not graphed because they should not change. They could, however, be graphed as a verification that other conditions are not changing.

For example, after graphing the growth as compared to light, you could also look at how the temperature varied across different conditions. If you notice that it did vary quite a bit, you may need to go back and look at your experimental setup: How could you improve the experiment so that all plants are exposed to as similar an environment as possible (aside from the light color)?

How to Remember Which is Which

In order to try and remember which is the dependent variable and which is the independent variable, try putting them into a sentence which uses "causes a change in."

Here's an example. Saying, "light color causes a change in plant growth," is possible. This shows us that the independent variable affects the dependent variable. The inverse, however, is not true. "Plant growth causes a change in light color," is not possible. This way you know which is the independent variable and which is the dependent variable!

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• NCES Kids: What are Independent and Dependent Variables?
• Khan Academy: Dependent and independent variables review (article)

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Riti Gupta holds a Honors Bachelors degree in Biochemistry from the University of Oregon and a PhD in biology from Johns Hopkins University. She has an interest in astrobiology and manned spaceflight. She has over 10 years of biology research experience in academia. She currently teaches classes in biochemistry, biology, biophysics, astrobiology, as well as high school AP Biology and Chemistry test prep.

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Independent and Dependent Variables Examples

The independent and dependent variables are key to any scientific experiment, but how do you tell them apart? Here are the definitions of independent and dependent variables, examples of each type, and tips for telling them apart and graphing them.

Independent Variable

The independent variable is the factor the researcher changes or controls in an experiment. It is called independent because it does not depend on any other variable. The independent variable may be called the “controlled variable” because it is the one that is changed or controlled. This is different from the “ control variable ,” which is variable that is held constant so it won’t influence the outcome of the experiment.

Dependent Variable

The dependent variable is the factor that changes in response to the independent variable. It is the variable that you measure in an experiment. The dependent variable may be called the “responding variable.”

Examples of Independent and Dependent Variables

Here are several examples of independent and dependent variables in experiments:

• In a study to determine whether how long a student sleeps affects test scores, the independent variable is the length of time spent sleeping while the dependent variable is the test score.
• You want to know which brand of fertilizer is best for your plants. The brand of fertilizer is the independent variable. The health of the plants (height, amount and size of flowers and fruit, color) is the dependent variable.
• You want to compare brands of paper towels, to see which holds the most liquid. The independent variable is the brand of paper towel. The dependent variable is the volume of liquid absorbed by the paper towel.
• You suspect the amount of television a person watches is related to their age. Age is the independent variable. How many minutes or hours of television a person watches is the dependent variable.
• You think rising sea temperatures might affect the amount of algae in the water. The water temperature is the independent variable. The mass of algae is the dependent variable.
• In an experiment to determine how far people can see into the infrared part of the spectrum, the wavelength of light is the independent variable and whether the light is observed is the dependent variable.
• If you want to know whether caffeine affects your appetite, the presence/absence or amount of caffeine is the independent variable. Appetite is the dependent variable.
• You want to know which brand of microwave popcorn pops the best. The brand of popcorn is the independent variable. The number of popped kernels is the dependent variable. Of course, you could also measure the number of unpopped kernels instead.
• You want to determine whether a chemical is essential for rat nutrition, so you design an experiment. The presence/absence of the chemical is the independent variable. The health of the rat (whether it lives and reproduces) is the dependent variable. A follow-up experiment might determine how much of the chemical is needed. Here, the amount of chemical is the independent variable and the rat health is the dependent variable.

How to Tell the Independent and Dependent Variable Apart

If you’re having trouble identifying the independent and dependent variable, here are a few ways to tell them apart. First, remember the dependent variable depends on the independent variable. It helps to write out the variables as an if-then or cause-and-effect sentence that shows the independent variable causes an effect on the dependent variable. If you mix up the variables, the sentence won’t make sense. Example : The amount of eat (independent variable) affects how much you weigh (dependent variable).

This makes sense, but if you write the sentence the other way, you can tell it’s incorrect: Example : How much you weigh affects how much you eat. (Well, it could make sense, but you can see it’s an entirely different experiment.) If-then statements also work: Example : If you change the color of light (independent variable), then it affects plant growth (dependent variable). Switching the variables makes no sense: Example : If plant growth rate changes, then it affects the color of light. Sometimes you don’t control either variable, like when you gather data to see if there is a relationship between two factors. This can make identifying the variables a bit trickier, but establishing a logical cause and effect relationship helps: Example : If you increase age (independent variable), then average salary increases (dependent variable). If you switch them, the statement doesn’t make sense: Example : If you increase salary, then age increases.

How to Graph Independent and Dependent Variables

Plot or graph independent and dependent variables using the standard method. The independent variable is the x-axis, while the dependent variable is the y-axis. Remember the acronym DRY MIX to keep the variables straight: D = Dependent variable R = Responding variable/ Y = Graph on the y-axis or vertical axis M = Manipulated variable I = Independent variable X = Graph on the x-axis or horizontal axis

• Babbie, Earl R. (2009). The Practice of Social Research (12th ed.) Wadsworth Publishing. ISBN 0-495-59841-0.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 978-0-521-29925-1.
• Gauch, Hugh G. Jr. (2003). Scientific Method in Practice . Cambridge University Press. ISBN 978-0-521-01708-4.
• Popper, Karl R. (2003). Conjectures and Refutations: The Growth of Scientific Knowledge . Routledge. ISBN 0-415-28594-1.

Related Posts

Identifying Variables

Three types of tomatoes (MOs810, Wikimedia Commons)

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Learn how scientists define independent, dependent and controlled variables in experimental inquiry.

As was mentioned in the  Asking Testable Questions  backgrounder, testable questions define the variables. In other words, what is being changed and what is to be kept constant, in an experimental inquiry.

What are variables in an experimental inquiry?

Scientists often use experimental inquiries to observe cause and effect relationships. In order to do so, scientists aim to make one change (the cause or  independent variable ) in order to determine if the variable is causing what is observed (the effect or  dependent variable ).

An experimental inquiry typically has three main types of variables: an independent variable, a dependent variable and controlled variables. We will look at each of these three types of variables and how they are related to experimental inquiries involving plants.

Independent Variables

The independent variable, also known as the experimental treatment , is the difference or change in the experimental conditions that is chosen by the scientist (the cause). To ensure a  fair test , a good experimental inquiry only has  one  independent variable and that variable should be something that can be measured quantitatively. For example, experimental inquiries about plants may include such independent variables as:

• Volume of water given to plants
• Nitrogen or phosphorus concentration in soil
• Duration, intensity or wavelength of light plants are exposed to
• Concentration or type of fertilizer

Dependent Variables

When a scientist chooses an independent variable (the cause), that person anticipates a certain response (the effect). This response is known as the dependent variable. The dependent variable should be something that is observable and measurable. Like the independent variable, an experimental inquiry should only have one dependent variable. For example, experimental inquiries about plants may include such dependent variables as:

• Days to germination
• Surface area of leaves
• Days to flowering or fruiting
• Dry mass (amount of plant material after all water has been removed)

Testable Question

How does the volume of water affect the number of days it takes for a tomato plant to flower?

Shown is a colour illustration explaining the relationship between an independent and a dependent variable. 

On the left is a blue oval with the word "Cause" inside it. This is labelled "Independent Variable" at the top, and "E.g., volume of water" below. On the right is a green rectangle with the word "Effect" inside. This is labelled "Dependent Variable" at the top, and "E.g., days to flowering" below. A red arrow points from cause on the left to the effect on the right.

Controlled Variables

In order for a scientist to ensure that only the independent variable is affecting the dependent variable, all the other factors acting upon the test situation (or test subjects) must be kept constant. The factors that must be kept the same are called the  controlled variables , or constant variables. In a given inquiry, there may be one or more variables that will need to be kept constant. For example, for an experimental inquiry in which you are interested in how the volume of water (independent variable) affects the days to flowering (dependent variable), you would want to keep constant:

• The type of seeds
• The type of soil
• The light source
• The humidity in the room
• The type of container (e.g., plastic pots vs. clay pots)
• The Temperature

Shown is a colour photograph of tomato plants in a greenhouse. 

Rows of tomato plants on both sides of the photograph stretch into the distance. Light comes in through a translucent ceiling. The plants are thick with green leaves. Tomato fruit is visible at the bottom of each plant. Most of the fruit is red and some is green.

A failure to control variables other than the independent variable will mean that you will not know which factor is actually causing the effects you see. In the example above, if some of the plants were sitting closer to the window than others, the differential exposure to light could be affecting the number of days to flowering, rather than the volume of water.

For more about designing experiments, see:  Setting Up a Fair Test

What are the variables in Tomatosphere™?

In the Seed Investigation, students investigate the germination rates of tomato seeds that have been to space (or exposed to space-like conditions) with seeds that have remained on Earth.

The  testable question  in the Seed Investigation is:

HOW DOES EXPOSURE TO THE SPACE ENVIRONMENT OR SPACE-LIKE CONDITIONS AFFECT THE GERMINATION RATE OF TOMATO SEEDS?

Independent variable:  type of seeds used - Earth seeds versus space seeds (sometimes seeds are treated to space-like conditions in years when seeds do not go to space)

Dependent variable:  number of seeds that germinate

Guided Practice

Have students read the following questions and determine the independent, dependent and potential controlled variables.

• How does the duration of light exposure affect the surface area of tomato plant leaves?
• How does the concentration of nitrogen fertilizer affect the days to flowering of tomato plants?
• How does the volume of water (mL) affect the number of days to germination of tomato plants?

In their own words, have students define the terms “Independent variable,” “Dependent variable,” and “Controlled variable.”

Have students brainstorm the variables that should be controlled in the Seed Investigation (e.g., quantity of water, type of soil, type of planting container, temperature, etc.).

Have the students think about the Seed Investigation and brainstorm variables that may not be controllable (e.g., giving plants different amounts of water, some plants being closer to a heat vent than others, using different types of soil, etc.).

• Independent variable:   duration of light (hours) Dependent variable:   surface area of plant leaves (Overall? Largest leaf? All leaves?) Controlled variable(s):   quantity of water, type of soil, depth of seeds, source of light, concentration/type of fertilizer (if any); temperature of the room, etc.
• Independent variable:   Concentration of nitrogen fertilizer Dependent variable:   days to flowering (when first flower on plants open) Controlled variable(s):   Same type of seeds, same quantity of water, same type of soil, same source of light, same duration of light, etc.
• Independent variable:   Volume of water in ml (per day) Dependent variable:   days to germination (when first seed germinates) Controlled variable(s):   Single type of seeds, same type of soil, same volume of soil, same type of pots, same source of light, same duration of light, temperature of the room, same time of day for watering, etc.

What are variables? How to use them in your science projects This page from Science Buddies explains different sorts of variables and how to use them to answer sample questions.

Controlled Variables This article by Explorable covers variables, control groups, and the value of consistency.

What are Independent and Dependent Variables?  (2019) This article by ThoughtCo explains how to tell the difference between independent and dependent variables, and how to plot variables on a graph.

Identifying and Controlling Variables in Scientific Investigations  (2015) This video (3:16 min.) from SciExperiment Basics explains how to identify and control variables in a scientific inquiry.

Related Topics

Independent, Dependent and Controlled Variables

This is part of the NSW HSC science curriculum part of the Working Scientifically skills.

What are Independent, Dependent, and Controlled Variables?

As a high school science student, you are likely to come across different types of variables in your experiments. Being able to recognise these variables is a skill which is included in the NSW Higher School Certificate (HSC) curriculum. These variables are essential to scientific inquiry as they help us understand how different factors affect the outcomes of experiments. There are three main types of variables in scientific investigations: independent, dependent, and controlled variables. We will explore each of these variables and their importance in scientific inquiry. 

Independent Variables

Independent variables are the variables that are manipulated or changed by the researcher in an experiment. They are also known as the input variables or the cause variables because they are the factors that cause changes in the dependent variable.

For example, if you were investigating the effect of temperature on the rate of photosynthesis in plants, temperature would be the independent variable. You would manipulate the temperature to see how it affects the rate of photosynthesis.

It is essential to note that an experiment should have only one independent variable. This is because if you change more than one variable, you will not know which variable caused the change in the dependent variable. Therefore, by controlling the independent variable, you can determine the effect of that variable on the dependent variable.

Dependent variables

Dependent variables are the variables that are affected by the independent variable in an experiment. They are also known as the outcome variables or the effect variables. The dependent variable is what you measure or observe to determine the effect of the independent variable.

For example, in the temperature and photosynthesis experiment, the dependent variable would be the rate of photosynthesis, which is affected by changes in temperature.

It is crucial to keep the dependent variable constant during an experiment to ensure that any changes observed are a result of changes in the independent variable. Additionally, the dependent variable should be measurable and quantitative, meaning that it can be expressed in numerical values.

Controlled variables

Controlled variables are the variables that are kept constant during an experiment to ensure that they do not affect the outcome. These variables are also known as constant variables or the controlled factors. The purpose of controlling these variables is to ensure that any changes observed in the dependent variable are due to changes in the independent variable and not due to other factors.

For example, in the temperature and photosynthesis experiment, the controlled variables would include factors such as the type of plant, the amount of light, and the amount of carbon dioxide. By keeping these variables constant, you can ensure that any changes in the rate of photosynthesis are due to changes in temperature and not due to other factors.

Identifying variables

Let's consider a scenario where we want to investigate the effect of different amounts of water on plant growth. In this case:

Independent variable: The independent variable in this experiment is the amount of water used to water the plants. We could use different amounts of water, such as 100 ml, 200 ml, or 300 ml.

Dependent variable: The dependent variable is still the growth of the plants, which we could measure by tracking the height, weight, or number of leaves of the plants.

Controlled variables: Some controlled variables in this experiment might include the type and species of plants used, the type and amount of soil used, the size and type of pots used, and the amount of sunlight and temperature that the plants are exposed to.

By identifying and controlling these variables, we can design a more controlled and rigorous experiment to investigate the effect of different amounts of water on plant growth.

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Biology archive

Course: biology archive   >   unit 1.

• The scientific method

Controlled experiments

• The scientific method and experimental design

Introduction

How are hypotheses tested.

• One pot of seeds gets watered every afternoon.
• The other pot of seeds doesn't get any water at all.

Control and experimental groups

Independent and dependent variables, independent variables, dependent variables, variability and repetition, controlled experiment case study: co 2 ‍   and coral bleaching.

• What your control and experimental groups would be
• What your independent and dependent variables would be
• What results you would predict in each group

Experimental setup

• Some corals were grown in tanks of normal seawater, which is not very acidic ( pH ‍   around 8.2 ‍   ). The corals in these tanks served as the control group .
• Other corals were grown in tanks of seawater that were more acidic than usual due to addition of CO 2 ‍   . One set of tanks was medium-acidity ( pH ‍   about 7.9 ‍   ), while another set was high-acidity ( pH ‍   about 7.65 ‍   ). Both the medium-acidity and high-acidity groups were experimental groups .
• In this experiment, the independent variable was the acidity ( pH ‍   ) of the seawater. The dependent variable was the degree of bleaching of the corals.
• The researchers used a large sample size and repeated their experiment. Each tank held 5 ‍   fragments of coral, and there were 5 ‍   identical tanks for each group (control, medium-acidity, and high-acidity). Note: None of these tanks was "acidic" on an absolute scale. That is, the pH ‍   values were all above the neutral pH ‍   of 7.0 ‍   . However, the two groups of experimental tanks were moderately and highly acidic to the corals , that is, relative to their natural habitat of plain seawater.

Analyzing the results

Non-experimental hypothesis tests, case study: coral bleaching and temperature, attribution:, works cited:.

• Hoegh-Guldberg, O. (1999). Climate change, coral bleaching, and the future of the world's coral reefs. Mar. Freshwater Res. , 50 , 839-866. Retrieved from www.reef.edu.au/climate/Hoegh-Guldberg%201999.pdf.
• Anthony, K. R. N., Kline, D. I., Diaz-Pulido, G., Dove, S., and Hoegh-Guldberg, O. (2008). Ocean acidification causes bleaching and productivity loss in coral reef builders. PNAS , 105 (45), 17442-17446. http://dx.doi.org/10.1073/pnas.0804478105 .
• University of California Museum of Paleontology. (2016). Misconceptions about science. In Understanding science . Retrieved from http://undsci.berkeley.edu/teaching/misconceptions.php .
• Hoegh-Guldberg, O. and Smith, G. J. (1989). The effect of sudden changes in temperature, light and salinity on the density and export of zooxanthellae from the reef corals Stylophora pistillata (Esper, 1797) and Seriatopora hystrix (Dana, 1846). J. Exp. Mar. Biol. Ecol. , 129 , 279-303. Retrieved from http://www.reef.edu.au/ohg/res-pic/HG%20papers/HG%20and%20Smith%201989%20BLEACH.pdf .

Additional references:

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Plant Breeding and Genomics

Introduction to Experimental Design

Shawn C. Yarnes, The Ohio State University

Defining Variables and Experimental Units

Experimental design begins with the formulation of experimental questions , which help define the variables that will change in an experiment. Experimental treatments , or independent variables , are the controlled part of an experiment expected to affect the response , or dependent variables . The experimenter must identify which treatment and response variables will best answer experimental questions.

Consider the broad experimental question. How do plants respond to fertilizer application? This question must be made more specific to design an effective experiment. 

The dependent variable , plant response , can be defined and measured in numerous ways. If the experimenter is interested in plant growth and nitrogen content, the question can be made more specific by asking how does plant growth and nitrogen content change in response to fertilizer application? Determination of response variables is influenced by experimental objectives and practical considerations. For example, total dry weight is more accurate than height as a measurement of plant growth, but in the case of a tree experiment, height might be more practical.

The independent variable , fertilizer treatment , can also be defined in numerous ways that will help specify experimental questions. A single fertilizer treatment with different levels can be tested, or multiple fertilizers compared. Levels can be: qualitative, or categorical, as when denoting males and females in a population; or quantitative, such as different fertilizer concentrations. Levels can also be defined as fixed or random effects. Sex distribution in a population is generally a random effect ; while fertilizer application is an experimenter controlled, or  fixed effect . The decision to define a variable as fixed or random will affect future statistical analyses (See  Analysis of Variance (ANOVA): Experimental Design for Fixed and Random Effects ). 

Once response and experimental treatments are defined, proper control treatments must be determined. Controls are integral to the scientific method by providing baseline values against which other treatments are compared. Negative controls , such as non-fertilized plants in Example 1, are null treatments where no response is expected. The simplest experiment has one response variable, one negative control, and one treatment. If experimental results support a null hypothesis (H 0 ), no significant difference is observed between controls and other treatments. 

Positive controls are treatments where a known response is expected. Positive controls are often used to validate assays or equipment functioning. For example, many enzyme kits come with pre-digested substrates, so that experimental digestions can be deemed successful compared to the positive control. Positive controls can also be used to calibrate or standardize measurements. For example, a standard curve of known substrate concentrations can be used to calculate the amount of unknown substrate concentrations.  

Experimental units must be defined during experimental design. The experimental unit is an individual, object, or plot subjected to treatment independently of other units. The number of experimental units is the sum of all treatments, levels, and and replicates. When experimental units are sampled only once, the experimental unit and sampling unit  are the same. The experimental unit can also be comprised of multiple sampling units. When experimental units are heterogeneous for the response variable, the mean of multiple sample units can be more precise than a single measure.  For example, if leaf nitrogen content is variable between leaves, an experimenter may choose to measure the nitrogen content from multiple leaves, using the mean nitrogen content to represent the individual plant.  Increasing the sampling units does not increase replication.

Planning for Statistical Inference

The goal of an experiment is to detect differences between treatments. Statistical determination of these differences requires replication to compute experimental error and randomization to help ensure that the measure of experimental error is valid. Discussions of experimental error and replication become circular, because replications are needed to compute experimental error, and the number of replications needed is based on the magnitude of experimental error. Experimental design requires an a priori estimation of error. In some situations a preliminary study is used to estimate error. In other situations error is inferred using reasonable assumptions based on the current understanding of the study system.

Experimental Error

Experimental error is the variation among experimental units within the same treatment group. There are many possible reasons for error. Errors within an experiment are additive. Reducing the amount of error in an experiment increases your ability to detect significant differences between treatments. A well-designed experiment considers the error contributed by both natural variation and lack of experimental uniformity.

Natural variation is a large component of error in biological experiments. Genetic and developmental differences, as well as differences in species abundance and diversity, can vary between experimental units. In plant breeding, clones and inbreed lines are often utilized to reduce genetic variation between experimental units. 

Lack of experimental uniformity is the source of error over which an investigator has the most control. Although there is always an imperfect ability to provide identical environments for each experimental unit, identifying and controlling error is essential. Errors in technique and/or data recording can inflate estimated experimental error (decrease precision) and introduce bias into the results (decrease accuracy).

Relationship Between Error and Sample Size

The sample size needed to detect differences between treatments increases with error. This is the reason biological field experiments generally require larger sample sizes than more controlled laboratory experiments. Experimental effort and expense are directly proportional to sample size. For these reasons controlling error is the focus of every investigator.  

The graph below illustrates the realtionship between error (σ), sample size, and the ability to detect differences between two means. (See  Estimating Sample Size for Comparison of Two Means and  Equation to Estimate Sample Size Required for QTL Detection ).

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Science project, how light affects plant growth.

Purpose : The purpose of this project is to show that different colors of light affect the development of plants.

Hypothesis : I predict that plants will grow better under blue, red and yellow lights than they will under white and green lights.

Background : The relationship between light and plant growth can be demonstrated by exposing leaves to various colors of light. Light supplies the power to carry on photosynthesis, the food-making process in leaves. But the spectrum of light most utilized by a leaf is limited to three distinct colors, red, blue and yellow. For example, leaves appear green because green is the color most leaves reflect rather than absorb and use.

Independent Variable : Color of light

Dependent Variable : Plant height

Control Variables : Same size soybean plants, fertilizer, soil, water, potting soil, colored filters, 10 gallon aquarium tank.

Procedures : Plant four soybean plants of the same size in an aquarium containing 5" of well moistened potting soil. Apply the recommended dosage of fertilizer. Place a colored filter tent over each plant. One filter should be clear. Use blue, yellow, and red film for the other filters. Place the aquarium in direct sunlight. Keep in the same location during the experiment and water daily. Measure each plant every day and record your findings in a notebook. Be sure to measure from the bottom of the aquarium and not the surface of the potting soil.

Materials : All the materials for this project are available locally. You can obtain a 10 gallon aquarium from a pet shop. Office stores sell colored transparency sheets. Most garden supply shops sell soybean seeds, potting soil and plant feretilizer. Be sure to germinate your soybean plants to a height of 4" before beginning your experiment.

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Methodology

• Control Variables | What Are They & Why Do They Matter?

Control Variables | What Are They & Why Do They Matter?

Published on March 1, 2021 by Pritha Bhandari . Revised on June 22, 2023.

A control variable is anything that is held constant or limited in a research study. It’s a variable that is not of interest to the study’s objectives , but is controlled because it could influence the outcomes.

Variables may be controlled directly by holding them constant throughout a study (e.g., by controlling the room temperature in an experiment), or they may be controlled indirectly through methods like randomization or statistical control (e.g., to account for participant characteristics like age in statistical tests). Control variables can help prevent research biases like omitted variable bias from affecting your results.

Table of contents

Why do control variables matter, how do you control a variable, control variable vs. control group, other interesting articles, frequently asked questions about control variables.

Control variables enhance the internal validity of a study by limiting the influence of confounding and other extraneous variables . This helps you establish a correlational or causal relationship between your variables of interest and helps avoid research bias .

Aside from the independent and dependent variables , all variables that can impact the results should be controlled. If you don’t control relevant variables, you may not be able to demonstrate that they didn’t influence your results. Uncontrolled variables are alternative explanations for your results and affect the reliability of your arguments.

Control variables in experiments

In an experiment , a researcher is interested in understanding the effect of an independent variable on a dependent variable. Control variables help you ensure that your results are solely caused by your experimental manipulation.

The independent variable is whether the vitamin D supplement is added to a diet, and the dependent variable is the level of alertness.

To make sure any change in alertness is caused by the vitamin D supplement and not by other factors, you control these variables that might affect alertness:

• Timing of meals
• Caffeine intake
• Screen time

Control variables in non-experimental research

In an observational study or other types of non-experimental research, a researcher can’t manipulate the independent variable (often due to practical or ethical considerations ). Instead, control variables are measured and taken into account to infer relationships between the main variables of interest.

To account for other factors that are likely to influence the results, you also measure these control variables:

• Marital status

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There are several ways to control extraneous variables in experimental designs, and some of these can also be used in observational studies or quasi-experimental designs.

Random assignment

In experimental studies with multiple groups, participants should be randomly assigned to the different conditions. Random assignment helps you balance the characteristics of groups so that there are no systematic differences between them.

This method of assignment controls participant variables that might otherwise differ between groups and skew your results.

It’s possible that the participants who found the study through Facebook use more screen time during the day, and this might influence how alert they are in your study.

Standardized procedures

It’s important to use the same procedures across all groups in an experiment. The groups should only differ in the independent variable manipulation so that you can isolate its effect on the dependent variable (the results).

To control variables , you can hold them constant at a fixed level using a protocol that you design and use for all participant sessions. For example, the instructions and time spent on an experimental task should be the same for all participants in a laboratory setting.

• To control for diet, fresh and frozen meals are delivered to participants three times a day.
• To control meal timings, participants are instructed to eat breakfast at 9:30, lunch at 13:00, and dinner at 18:30.
• To control caffeine intake, participants are asked to consume a maximum of one cup of coffee a day.

Statistical controls

You can measure and control for extraneous variables statistically to remove their effects on other types of variables .

“Controlling for a variable” means modelling control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

A control variable isn’t the same as a control group . Control variables are held constant or measured throughout a study for both control and experimental groups, while an independent variable varies between control and experimental groups.

A control group doesn’t undergo the experimental treatment of interest, and its outcomes are compared with those of the experimental group. A control group usually has either no treatment, a standard treatment that’s already widely used, or a placebo (a fake treatment).

Aside from the experimental treatment, everything else in an experimental procedure should be the same between an experimental and control group.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

“Controlling for a variable” means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

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VanCleave's Science Fun

Your Guide to Science Projects, Fun Experiments, and Science Research

Variables: Independent, Dependent, Controlled

By Janice VanCleave

Types of Variables in A Science Fair Project

Independent variables Dependent variables Controlled variables

Example: Investigate Electromagnetics

———————————————————–

Example: Investigate Plant Growth

List what you know about plant growth.

  Following are more examples of variables.

A variable is part of an experiment that can change, such as the amount of light, temperature, humidity, or plant growth as well as the direction of plant growth.

In an experiment, an independent variable is a variable that changes either on its own, or you purposely change it. For example, you can control the amount of light, environmental temperature,  and humidity in which a plant is grown.

The goal of an experimental investigation is to determine how changes in an independent variable affects another variable, which is called the dependent variable. 

Remember: When designing an Experimental Investigation  it is important that you only have one independent variable and one dependent variable. All other variables must be controlled, meaning they must stay the same.   

FYI: Controlled variables are not the same as a Control for your Investigation. The following will explain this.

Start Experiment Design:

I want you to understand some of the thought processes for designing an experiment that meets Science Fair Project requirements.

1. You need to have a purpose for your investigation. At this point you may not know exactly what you want to do, but  let’s assume you want to work with plants. I’d search the web and find different project ideas about plants.

Let’s assume you decide to investigate how light affects plant growth. At this point you need to write a basic purpose. I point out that this might only be a   BASIC Purpose , meaning you may need to improve it.

Basic Purpose of Investigation:  How light affects plant growth.

I’ll come back to the purpose, but next you need to write your science fair question.

2. The question for an experimental investigation must identify both the independent variable and the dependent variable. Your basic purpose identifies light as the independent variable and plant growth as the dependent variable.

Don’t Forget:  The independent variable and the dependent variable for an experimental investigation must be measurable.

Measuring the Independent Variable

How does one measure light? Light is very general. You need to be more specific about the independent variable. You will get the point after reading the following questions.

• Do you want to measure how different types of light sources, such as sunlight, artificial light, or colored light affects plant growth?   This is a good idea for a science project.
• Do you want to measure how changes in the amount of one type of light effects plants growth? This is another good idea for a science project.

You may have other ideas about the light you want to use, but for this article, I will give examples for measuring the amount of one type of light.

The Independent Variable is the amount of light the plant received.

Ideas for how to change the amount of light.

1. Use sunlight, which changes during the day as well as from one day to the next. You can also use direct and indirect sunlight.

2. If you use artificial light you can decide when and for how long the plant will receive this light. You also have the option to control the wattage of light used–its color–type (fluorescent, UV, incandescent). Just use the same type of light for each test plant.

Dependent Variable

The purpose of  changing an independent variable is to decide how the changes affect something else, which is called the dependent variable. In other words, changes in the independent variable may cause the dependent variable to change.

In an experiment, a dependent variable may change due to the changes made in the independent variable.

For the earlier plant experiment, “How Plants Grow In Response to Light,”  the growth of the plant is the dependent variable being observed  The plant growth is in response to changes in the amount of light the plant receives, is the independent variable.

Controlled Variables

Controlled variables sounds like an oxymoron. Just remember that variables are things that CAN change. This means that they can be controlled and prevented from changed.

It is important that when you experiment that you have only two variables that change:

• The independent variable that you want to change and can measure how it changes.
• The dependent variable that you are measuring to see how much it changes in response to the independent variable.

Changes in any other variable could affect your results.  So, you must try to control any other variable,  meaning you want to delete them if possible, or at least make an effort to reduce their influence if possible.

For example, in the previous experiment, “How Plants Grow In Response to Light,” the  variables that must be controlled include;

• the type of plant tested,
• type of soil, temperature,
• amount of water,
• type of light

These variables need to be the same for every plant tested. Some variable are difficult to control, but you should try to make every effort to keep them the same during the testing.

Use the Search on this website to find more examples of variables, one that parallels the information on this page, but provides another example, is The Variables of Testing Onions In a Hay Filled Bathtub.

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Unveiling Genotypic Response of Chickpea to Moisture Stress Based on Morpho‑Physiological Parameters in the Eastern Indo‑Gangetic Plains

• Choudhary, Arbind K.
• Dwivedi, Sharad Kumar
• Raman, Rohan Kumar
• Kumar, Saurabh
• Kumar, Rakesh
• Kumar, Santosh
• Dubey, Rachana
• Bhakta, Narayan
• Shubha, Kumari

In the eastern Indo‑Gangetic plains, chickpea is grown postrice cultivation mostly under rainfed condition with residual soil moisture which adversely affects branching as well as pod and seed development, ultimately resulting in substantial yield losses. The current study analysed the moisture stress response of 12 chickpea genotypes with control for different morpho‑physiological traits in two sets of field experiments carried out during the year 2017–18 and 2018–19. The current study observed varying response of chickpea genotypes under moisture stress condition with average yield reduction from 11.79% to 24.77%. Mean yield of genotypes under stress condition showed a strong positive association with yield index (1.00**) and stress tolerance index (0.915**). The biplot principal component analysis revealed maximum potential of three chickpea genotypes (DBGC 1, Pusa 256 and DBGC 2) for grain yield and biological yield under moisture stress condition. The correlation analysis showed a significant association of yield with physiological parameters such as photosynthetic rate (0.363**), stomatal conductance (0.364**) and transpiration rate (0.292*). The three higher yielding genotypes relatively maintained biological yield, yield plant−1, 100 seed weight and photosynthesis rate and showed reduced rates of stomatal conductance and transpiration under moisture stress condition. The study found variable genotypic response to moisture stress and showed that yield index as well as stress tolerance index was more effective to identify superior genotypes for moisture stress condition. The superior genotypes identified in the present study may be considered for rainfed areas of eastern Indo‑Gangetic plains and can be used in future chickpea breeding programs for drought tolerance.

Varying soil moisture and pH with alpine meadow degradation affect nitrogen preference of dominant species

• Original Paper
• Published: 03 August 2024

Cite this article

• Chimin Lai 1 ,
• Qiwu Hu 1 ,
• Jianbo Sun 2 , 3 ,
• Chengyang Li 4 ,
• Xiaojie Chen 2 , 3 ,
• Ben Chen 2 , 3 ,
• Xian Xue 2 ,
• Ji Chen 5 ,
• Fujiang Hou 6 ,
• Gang Xu 6 ,
• Wuchen Du 6 ,
• Carly Stevens 7 ,
• Fei Peng   ORCID: orcid.org/0000-0003-0912-3069 2 &
• Jun Zhou 8  

12 Accesses

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While it is established that dominant plant species of alpine meadows showed differential preference for N forms (ammonia, nitrate, and amino acids) under various degradation stages, the perseverance of the N-uptake preference and its affecting factors remains unknown. This is an important consideration because it determines efficacy of nutrient additions for restoration of degraded alpine meadows. An indoor pot experiment was conducted to investigate the plasticity and determinants of different plant species’ N-uptake preference using 15 N-labeled inorganic N ( 15 NH 4 + and 15 NO 3 − ) and one of dual-labeled ( 13 C- 15 N) amino acid (glycine). In the experiment, dominant species of alpine meadow from specific degradation status were planted in soils of alpine meadows with three different degradation status. Most species preferred to uptake nitrate in all soils, except the Kobresia humilis , Carex moorcroftii , and Aster flaccidus planted in the soil of severely degraded alpine meadow (SD-soil) that take up more ammonia. The relative abundance of different available N forms directly affects the N-uptake preferences of all species. The partial correlations between percentage uptake and availability of various N forms were different with the zero-order correlations when either soil moisture or pH was controlled. Differences in soil moisture and pH among the three alpine meadows affects the N uptake preference of the nine species through their impacts on the relative abundance of different available N forms. In conclusion, the differences in soil moisture and pH among soils of alpine meadows under different degradation statuses influence the relative abundance of various available N forms, thereby affecting the plant N uptake.

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Acknowledgements

This study was financially supported by the National Natural Science Foundation of China (42301345), West Light Foundation of The Chinese Academy of Sciences (xbzg-zdsys-202316).

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School of Geography and Environment, Jiangxi Normal University, Nanchang, China

Chimin Lai & Qiwu Hu

Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

Jianbo Sun, Xiaojie Chen, Ben Chen, Xian Xue & Fei Peng

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China

Jianbo Sun, Xiaojie Chen & Ben Chen

Department of Geography, Lingnan Normal University, Zhanjiang, China

Chengyang Li

Beiluhe Observation and Research Station on Frozen Soil Engineering and Environment in Qinghai-Tibet Plateau, Chinese Academy of Sciences, Lanzhou, China

State Key Laboratory of Grassland Argo-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture, Lanzhou University, Lanzhou, China

Fujiang Hou, Gang Xu & Wuchen Du

Lancaster Environment Centre, Lancaster University, Lancaster, UK

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Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China

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Fei Peng, Chimin Lai, and Jun Zhou conceived the ideas and designed the experiment; Chimin Lai, Jianbo Sun, Chengyang Li, Ben Chen and XiaoJie Chen collected and analyzed the samples; Chimin Lai analyzed the data; Chimin Lai and Fei Peng prepared the figures and wrote the manuscript; Fei Peng, Jun Zhou, Ji Chen, Fujiang Hou, Gang Xu, Wuchen Du and Carly Stevens revised and edited the draft.

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Lai, C., Hu, Q., Sun, J. et al. Varying soil moisture and pH with alpine meadow degradation affect nitrogen preference of dominant species. Biol Fertil Soils (2024). https://doi.org/10.1007/s00374-024-01853-6

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DOI : https://doi.org/10.1007/s00374-024-01853-6

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Describe a laboratory-based experiment you could carry out to investigate the effect of temperature on the rate of feeding of dog whelks on barnacles. Your answer should include references to the control of variables and the collection of quantitative data

A laboratory-based experiment could be carried out to investigate the effect of temperature on the rate of feeding of dog whelks on barnacles. The experiment could involve placing a number of dog whelks and barnacles into a large aquarium with a temperature control mechanism .

The aquarium would be divided into two sections, with one side heated and the other side kept at room temperature . The temperature in the heated section could be incrementally increased and the rate of feeding of the dog whelks on the barnacles monitored over time.

To ensure accuracy, the experiment should be repeated a number of times with different temperatures, and the results should be compared with those of a control group kept at a constant room temperature. The experiment should also be carried out in a controlled environment with other variables such as light, humidity and salinity held constant.

By measuring the rate of feeding of the dog whelks on the barnacles over time for each temperature, quantitative data could be collected in order to determine the effect of temperature on the rate of feeding.

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Related Questions

_______ are sentence frames that help identify the number of participants involved in the event or situation described by a sentence. A) Information structures b) Verbal structures c) Argument structures d) Linguistic structures

C. Argument structures.

Explanation:

Argument structures are sentence frames that help identify the number of participants involved in the event or situation described by a sentence.

which statement best accounts for the hereditary transmission of sdh-linked paraganglioma in a parent specific manner? sdh is: a.an imprinted gene. b.a y-linked gene. c.an x-linked gene. d.a tumor suppressor gene.

The statement that best accounts for the hereditary transmission of SDH-linked paraganglioma in a parent-specific manner is an imprinted gene. So the correct answer is option: a.

An imprinted gene is a gene that is expressed in a parent-of-origin specific manner. This means that  expression of the gene depends on whether it was inherited from the mother or the father. In the case of SDH-linked paraganglioma, the disease is caused by mutations in genes that encode subunits of succinate dehydrogenase (SDH) enzyme. This parent-specific inheritance pattern suggests that the SDH genes may be imprinted, meaning that their expression is regulated by epigenetic mechanisms that differ depending on whether the gene was inherited from the mother or the father. Correct answer : a.

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The somatic and autonomic reflex pathways both consist of three neurons. Choose the three neurons that apply to the somatic reflex ONLY. A. Interneuron B. Post-Ganglionic neuron C. Sensory neuron D. Motor neuron E. Pre-Ganglionic neuron

The 3 neurons that apply the somatic reflex are

The function of the sensory neuron is to carry information and data from the receptor to the spinal cord.

The interneuron is present in the spinal cord and is connected to the sensory neuron with the help of a motor neuron .

The motor neuron helps to carry data and information from the spinal cord to an effector, hence presenting a response.

A somatic reflex refers to the that is involuntary stimulus received from the external environment .  For this process to be dynamic the responses from the receptors directly transfer the signals to directly to the spinal cord.    

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in the ecological pyramid, the amount of potential food available for each trophic level

10% of the energy is transferred at each trophic level.

Producers: 100,000 kJ

Herbivores: 10,000 kJ

Carnivores: 1,000 kJ

during its lifetime, a diploid (2n) plant acquires a mutation that causes it to produce diploid (2n) gametes. if this plant were to reproduce with another mutant plant that also produces diploid (2n) gametes, what ploidy would their offspring have?

The offspring of two diploids (2n) plants that produce diploid (2n) gametes will also be diploid (2n) because the gametes, which are haploid (n) in normal plants, carry only one set of chromosomes , in this case, the gametes carry two sets of chromosomes, resulting in a diploid zygote upon fertilization.

In diploid organisms, including plants, each cell has two sets of chromosomes , one from each parent. During sexual reproduction, the haploid gametes (sperm and egg cells) combine to form a diploid zygote with a complete set of chromosomes.

However, when a diploid plant acquires a mutation that causes it to produce diploid gametes, these gametes will have two sets of chromosomes, resulting in a diploid zygote upon fertilization .

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Is there a person in the room with whom you share all of the same traits? How can this be possible in the two of you are not related?

It is highly unlikely for any two individuals to share all the same traits, even if they are related. While two people may share some similar traits , it is unlikely for them to have all the same traits unless they are identical twins who share the same genetic code.

It is extremely unlikely for two unrelated individuals to share all the same traits, including physical characteristics, personality, interests, and behaviors. Even identical twins, who share the same genetic code, may exhibit some differences in their traits due to environmental factors and experiences that can shape their development and personality.

The reason for this is that traits are influenced by a complex interplay of genetic and environmental factors. While genetics can play a role in determining certain traits, such as physical characteristics or predispositions to certain health conditions, environmental factors such as upbringing, culture, and experiences can also have a significant impact on a person's traits.

Therefore, it is highly unlikely for two individuals to share all the same traits, as even the slightest differences in their genetic makeup or life experiences can lead to differences in their traits.

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Humans are a type of ___ mammal, having and organ that provides nutrients to the developing offspring.

Humans are a type of placental mammal, having an organ called the placenta that provides nutrients to the developing offspring .

Placental mammals , also known as Eutherians, are a diverse group of mammals that give birth to live young, which develop inside the mother's body. The placenta is a temporary organ that attaches to the uterine wall and allows for the exchange of oxygen, nutrients, and waste products between the mother and the developing fetus. This organ is vital for the survival and development of the fetus, providing a constant supply of nutrients and oxygen while also removing waste products.

Placental mammals make up the majority of all mammal species and include a wide range of animals such as dogs, cats, elephants, and humans. The placenta is a unique feature of this group of mammals and is one of the key adaptations that have allowed them to evolve and thrive in a variety of environments .

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6. Snyder ends her talk by saying, "Darwin knew what we seem to have forgotten, that science is not only for scientists. " What do you think that is meant by this? Do you consider yourself to have a basic scientific literacy? Explain and discuss your thoughts.

Snyder's speech emphasize the significance of owning our own media literacy and using it to make informed decisions. Being media literate is an ongoing process, and we must constantly work on developing and refining our abilities.

In her talk, Snyder ends by saying, "We are the ones we've been waiting for." This statement implies that the responsibility of promoting media literacy and critical thinking lies with each individual person. It means that we should not wait for others to provide us with the necessary tools to navigate the complex media landscape. Instead, we should take an active role in developing our own media literacy skills and using them to make informed decisions. Regarding the question of whether I consider myself to be media literate, I would say that I am continually working to improve my skills. With the abundance of information available today, it is essential to develop the ability to evaluate sources critically, identify biases, and recognize misinformation. I believe that being media literate is an ongoing process, and it requires a willingness to engage in lifelong learning. In conclusion, Snyder's statement emphasizes the importance of taking responsibility for our own media literacy and using our skills to make informed decisions. Being media literate is an ongoing process, and it is essential to continuously work on developing and refining our skills.

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What is the hybridization for xe in the xef2 molecule?.

The hybridization for Xe in the XeF₂ molecule is sp³d. Hybridization refers to the process of combining atomic orbitals to form new hybrid orbitals that are optimized for bonding. In the case of XeF₂, Xenon (Xe) is the central atom, and it forms two bonds with Fluorine (F) atoms.

To determine the hybridization of Xe in XeF₂ , we count the number of bonds and lone pairs around the central atom. In XeF₂, there are two bonding pairs and three lone pairs around Xe. This gives us a total of five electron pairs, which indicates that the hybridization of Xe is sp³d.

The sp³d hybrid orbitals of Xe allow it to form two sigma bonds with the F atoms by overlapping with their p orbitals. The three lone pairs of Xe occupy three of the hybrid orbitals, which give the molecule its linear shape.

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How do white blood cells compare to red blood cells?.

White blood cells and red blood cells are two types of cells found in the bloodstream , and they differ in their structure, function, and characteristics.

Red blood cells, also known as erythrocytes , are the most abundant cells in the bloodstream, responsible for carrying oxygen from the lungs to the body's tissues. They are small, disk-shaped cells without a nucleus, filled with hemoglobin protein. Hemoglobin gives red blood cells their distinctive red color and is responsible for binding and carrying oxygen molecules.

White blood cells, also known as leukocytes , are less abundant than red blood cells but are critical components of the immune system . They are larger than red blood cells and have a nucleus. There are several types of white blood cells, each with a specific function in fighting infections, including phagocytosis (engulfing and destroying pathogens), producing antibodies, and coordinating immune responses.

In summary, while red blood cells are primarily responsible for oxygen transport, white blood cells play a crucial role in defending the body against infections and diseases.

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Can anyone write down what the handwriting says?? I can’t read some parts of it

this organ produces enzymes that break down nutrients. What the name of this organ?

The Pancreas! Your Pancreas makes a digestive juice that has enzymes that break down carbohydrates, fats and proteins.

The organ that produces enzymes to break down nutrients is the pancreas .

The pancreas is a glandular organ located in the abdomen, behind the stomach. It has two main functions: exocrine and endocrine. The exocrine function of the pancreas is to secrete enzymes that aid in digestion. These enzymes include amylase, which breaks down carbohydrates; lipase, which breaks down fats; and proteases, which break down proteins. The pancreas also produces bicarbonate , a base that neutralizes stomach acid as it enters the small intestine. The endocrine function of the pancreas is to secrete hormones such as insulin and glucagon, which regulate blood sugar levels. Insulin lowers blood sugar levels, while glucagon raises them. The pancreas plays a crucial role in the digestive and endocrine systems and is essential for maintaining overall health. To know more about pancreas , refer here:

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What event is necessary for a virus to move genes from one organism to another?.

For a virus to move genes from one organism to another, it needs to undergo a process called " viral transmission ."

Viral transmission occurs when a virus leaves its host organism and enters a new host. This can happen in several ways, including direct contact between hosts, transmission through bodily fluids, or transmission through intermediate vectors (such as mosquitoes or ticks).

Once the virus has entered the new host, it may be able to infect cells and begin replicating, potentially leading to the transfer of viral genes to the host genome . This process is known as "viral integration" and can occur in both prokaryotic and eukaryotic organisms.

Viral transmission and integration are important mechanisms for the spread of viral genes and can have significant consequences for the evolution of both the virus and the host organism. For example, viral integration can lead to the development of new viral strains or even the acquisition of beneficial traits from the virus by the host organism.

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The mechanism by which the end product of a metabolic pathway inhibits an enzyme that catalyzes an earlier step in the pathway is most precisely described as Group of answer choices feedback inhibition cooperativity inhibition irreversible inhibition competitive inhibition

The mechanism by which the end product of a metabolic pathway inhibits an enzyme that catalyzes an earlier step in the pathway is most precisely described as feedback inhibition . The correct answer is option a.

Feedback inhibition is a regulatory mechanism that allows a cell to control the rate of a metabolic pathway by using the end product of the pathway as a signal to inhibit an earlier enzyme in the pathway. This inhibition reduces the rate of the pathway and prevents the accumulation of excess products.

Feedback inhibition is a type of reversible inhibition, which means that the inhibition can be relieved if the concentration of the end product decreases or if a different signal overrides the inhibition.

This is in contrast to irreversible inhibition, which permanently inactivates the enzyme, or competitive inhibition, which occurs when a molecule similar to the substrate binds to the active site of the enzyme and prevents the substrate from binding.

So, the correct answer is option a.

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The question is:

The mechanism by which the end product of a metabolic pathway inhibits an enzyme that catalyzes an earlier step in the pathway is most precisely described as

a) feedback inhibition

b) cooperative inhibition

c) irreversible inhibition

d) competitive inhibition

Explain the relationship between the dewdrop spider and the nephila spider

The dewdrop spider (Araneus marmoreus) and the nephila spider (Nephila clavipes) are two species of arachnids that are closely related and share many similarities.

Both spiders belong to the same family, Araneidae, and both build orb- shaped webs with an intricate radial pattern. They also both have a large, round abdomen, and their colors are similar – both have a gray or brown body and yellowish-green legs.

The main difference between the two is that the dewdrop spider is much smaller – only 8-12 mm in length compared to the nephila spider’s 20-30 mm. The nephila spider is also more aggressive, and its webs are often much larger.

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The compounds that Miller and Urey used in their experiment were probably not found on early Earth. Why are the results of their experiment still useful today?

Miller and Urey's experiment is still useful today despite the fact that the compounds used were not found on early Earth. The experiment was the first to demonstrate that organic molecules could be created from inorganic molecules and energy.

This provided a basis for the idea that organic molecules could have been the building blocks of life on Earth. Furthermore, the experiment provided insight into the chemical processes that are necessary for the formation of organic molecules and the role of energy in this process.

The experiment also showed that the building blocks of life can be created from inorganic compounds , which is useful for understanding the origin of life on Earth. The experiment is also useful for understanding the conditions that exist on other planets and moons in our solar system, and even outside of it.

Miller and Urey's experiment provided the groundwork for further investigations into the origin of life on Earth , and the conditions necessary for life to form and thrive elsewhere.

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An organism's niche is its? a. ideal climate b. source of food c. role in food chain d. maximum population

A niche is an organism’s role in its environment. It is an organism’s ideal climate, source of food, and role in the food chain .

Here, all the options are correct.

A niche is a very important part of an organism's life, as it defines the creature's place in its habitat. Every organism has a niche that determines how much food it can eat, what type of food it should eat, and what type of environment it should live in. A niche also determines the maximum population of an organism in its environment.

For example, a deer’s niche may be grazing in the grass of a meadow, while a fox’s niche may be hunting small mammals in the same meadow . Niches are integral to an organism's survival , as they help determine how much food it can eat and how it can best utilize its environment.

Niches also provide balance to a habitat, as an increase in one organism can lead to a decrease in another. Therefore, an organism’s niche is an important aspect of its life, as it not only helps determine its place in its habitat, but also helps to keep its environment in balance.

Therefore, all the options are correct.

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Is genetic engineering a boon or bane? Defend your answer​

Genetic engineering can be viewed as both a boon and a bane, depending on its applications and implications.

Genetic engineering has the potential to bring about numerous benefits. It allows for the development of genetically modified organisms (GMOs) with enhanced traits, such as disease resistance or increased crop yield, which can contribute to food security and agricultural sustainability. Genetic engineering also plays a crucial role in medical advancements, including the production of life-saving drugs and the potential for gene therapies to treat genetic disorders .However, there are also concerns and risks associated with genetic engineering. Unintended consequences and ecological impacts of GMOs on biodiversity and ecosystems need careful consideration. Ethical concerns arise regarding the modification of human germline cells, raising questions about the potential for eugenics and the long-term effects on future generations.To determine whether genetic engineering is a boon or bane, it is essential to evaluate its applications on a case-by-case basis, considering scientific, ethical, and societal factors. Striking a balance between the benefits and risks through comprehensive regulation, transparency, and public engagement is crucial to harnessing the potential of genetic engineering for the greater good while minimizing potential negative consequences.

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What are the ethical considerations in studying life processes?

Quite a few, here are some to think about:

1. Informed consent: Researchers should obtain informed consent from study participants, which means they must explain the nature of the study, potential risks and benefits, and allow participants to freely decide whether or not to participate.

2. Privacy and confidentiality: Researchers must protect the privacy and confidentiality of study participants by keeping their personal information and data confidential.

3. Respect for autonomy: Researchers must respect the autonomy of participants and allow them to make their own decisions about their participation in the study.

4. Animal welfare: When studying life processes using animals, researchers must consider the ethical treatment of animals and ensure that they are treated with respect and care.

5. Data integrity: Researchers must ensure the accuracy and integrity of data collected during the study and avoid falsification or manipulation of data.

6. Beneficence: Researchers must balance the potential benefits of the study against potential risks to participants and take steps to minimize harm to participants.

7. Social responsibility: Researchers must consider the potential impact of their research on society and ensure that their work is conducted in an ethical and socially responsible manner.

What is the phrase that reflects the idea that the superpowers would avoid nuclear war due to fear of mutual annihilation?.

The phrase that reflects the idea that the superpowers would avoid nuclear war due to fear of mutual annihilation is " mutually assured destruction " (MAD).

It was a concept developed during the Cold War , a political and military standoff between the United States and the Soviet Union, in which both countries possessed nuclear weapons.

The idea behind MAD was that if one country were to launch a nuclear attack on the other, the targeted country would respond with its own nuclear weapons, resulting in the total destruction of both countries.

This concept was meant to deter either side from initiating a nuclear war out of fear of the catastrophic consequences. Thus, MAD was a crucial part of the nuclear arms race between the superpowers and helped prevent a large-scale nuclear conflict during the Cold War era.

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What is the most important mechanism for transmitting qualitative information?.

The most important mechanism for transmitting qualitative information is through language. Language is a complex and highly developed system of communication that allows humans to convey ideas, emotions, and concepts using a set of agreed-upon symbols and rules.

It is a uniquely human ability that allows us to communicate not only basic needs but also complex and abstract concepts. Language is a dynamic system that can be spoken, written, or signed, and it is constantly evolving and adapting to meet the changing needs of society.

Through language, we are able to share knowledge, collaborate, and build communities, making it a crucial tool for social and cultural development .

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2. A species of wasp dies out in a prairie ecosystem. This species used to perform the important task of pollinating a widespread plant species. D This ecosystem will be less damaged by this local extinction if A. Most of the large animal species depend on the plant for food. B. The plant species also dies out. C. The wasp species is still successful in other ecosystems. D. There are other insect species that also pollinate the plant

There are other insect species that also pollinate the plant. Even though the specific wasp species that used to perform the important task of pollinating a widespread plant species is now extinct, there are likely other insect species in the prairie ecosystem that can perform the same task. The correct answer to this question is D.

This is because pollination is often carried out by multiple species of insects, and the loss of one species is not necessarily catastrophic for the ecosystem. Additionally, if most of the large animal species depend on the plant for food, then the loss of the wasp species could indirectly affect those animals as well.

Similarly, if the plant species also dies out, then the entire ecosystem could be impacted. Therefore, the most reasonable and optimistic scenario is that there are other insect species that also pollinate the plant, which can compensate for the loss of the wasp species and ensure that the prairie ecosystem remains relatively stable.

So, The correct answer to this question is D.

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Do all voltaic cells produce a positive cell potential?.

No, not all voltaic cells produce a positive cell potential. The cell potential, also known as the electromotive force (EMF), is a measure of the electric potential difference between two half-cells in a voltaic cell.

It is determined by the difference in the reduction potentials of the two half-cells. In some cases, the reduction potential of the half-cell containing the oxidizing agent can be higher than the reduction potential of the half-cell containing the reducing agent.

This can result in a negative cell potential, which means that the cell is not spontaneous and will require an external source of energy to operate.

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The enzyme dna polymerase reassembles the newly copied dna molecules. the enzyme helicase "reads" the original dna strand.

Enzyme "DNA polymerase" reconstructs newly copied DNA strands, while "helicase" unwinds the original DNA strand during replication .

An important role in DNA replication is played by the enzyme DNA polymerase, which adds complementary nucleotides to the template strand to form a new DNA strand. It guarantees purity and thoroughly checks the process. The double-stranded DNA molecule must unwind in order for the two strands to separate and form a replication fork, but helicase is also necessary to do this.

This makes it possible for DNA polymerase to function effectively. The unwinding process requires energy, which is done by breaking hydrogen bonds between base pairs. In order to transfer genetic information from one generation to the next, reliable DNA replication is essential, and both enzymes play important roles in the complex machinery that makes this possible.

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Your question is incomplete, most probably the complete question is:

The enzyme DNA polymerae reassembles the newly copied dna molecule while the enzyme helicae "reads" the original dna strand.

How is thermal energy within the earths layers of related to some of its natural disasters

Thermal energy within Earth's layers is related to some natural disasters, such as volcanic eruptions and earthquakes.

The Earth's interior contains significant heat, which is generated by radioactive decay and residual heat from the planet's formation. This thermal energy drives plate tectonics, which is the movement of Earth's lithosphere. Volcanic eruptions occur when magma, generated by the melting of Earth's mantle due to thermal energy, rises to the surface. This process can result in explosive eruptions and lava flows, causing widespread damage and posing risks to human life. Earthquakes , on the other hand, are often caused by the movement of tectonic plates, driven by the same thermal energy.

As plates move, they interact with each other, leading to the buildup of stress along faults. When this stress is released, it generates seismic waves, resulting in an earthquake. In conclusion, thermal energy within Earth's layers plays a crucial role in driving natural disasters like volcanic eruptions and earthquakes by influencing the movement of tectonic plates and the generation of magma.

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List the main components in our diet and state their function

The main components of a healthy diet are carbohydrates, proteins, fats, vitamins, minerals and water. Carbohydrates are the main source of energy for our bodies and are found in grains, legumes, fruits and vegetables .

Proteins are the building blocks of cells and are found in meats, eggs, nuts and dairy products. Fats help the body absorb vitamins and minerals and are found in oils, nuts and dairy products . Vitamins and minerals are essential for our bodies to function properly and are found in fruits, vegetables, whole grains and dairy products.

Each of these components provides our bodies with vital nutrients and energy. Carbohydrates are broken down into glucose, which is used by the body to provide energy. Proteins are used to build and repair cells and tissues, while fats help to transport vitamins and minerals around the body.

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The diversity of alleles and genotypes within a population is known as:.

genetic variance.

The diversity of alleles and genotypes within a population is known as genetic variance.

What five factors cause people to evaluate risk irrationally?

The five factors that can cause people to evaluate risk irrationally are: Affect Heuristic, Optimism Bias, Availability Heuristic, Confirmation Bias, Herding Behavior.

There are several factors that can lead people to evaluate risk irrationally. First, emotions can play a significant role in how people perceive risk. Fear, anxiety, and anger can all cause people to overestimate the likelihood of negative outcomes and make irrational decisions. Second, cognitive biases can also influence risk assessment .

Confirmation bias, for example, can cause people to seek out information that confirms their existing beliefs, leading them to ignore or downplay contradictory evidence. Third, people often rely on heuristics, or mental shortcuts, when making decisions about risk. These shortcuts can be useful in some situations, but they can also lead to errors in judgment. Fourth, social influences can also affect how people evaluate risk.

For example, people may be more likely to take risks if they believe that others are doing so as well. Finally, people may simply lack knowledge or information about the risks they face, which can lead them to make poor decisions.

To know more about risk click here:

https://brainly.com/question/17284407

What is a theme of how the death of patroclus roused achilles, the making of the arms, and the vengeance of achilles from the iliad?.

One of the themes of the death of Patroclus, the making of the arms, and the vengeance of Achilles from the Iliad is the importance of honor and glory in ancient Greek society .

Throughout the epic poem, the characters are driven by their desire for honor and glory , which are seen as essential components of their identity and status in society. When Patroclus is killed by Hector, Achilles is consumed by grief and rage, and he is motivated to seek revenge in order to restore his own honor and that of his fallen comrade.

In his quest for vengeance , Achilles seeks to demonstrate his strength and prowess in battle, and he does so by defeating Hector and dragging his body back to the Greek camp. The making of the arms, which are ornate and beautiful, also serves to showcase Achilles' skill and status as a warrior.

Ultimately, the death of Patroclus and the vengeance of Achilles highlight the central role of honor and glory in ancient Greek culture, and the lengths to which individuals were willing to go to defend their honor and reputation. This theme is a recurring motif throughout the Iliad and reflects the values and beliefs of ancient Greek society.

To know more about the Greek society refer here :

https://brainly.com/question/28934626#

How can failing to conserve water contribute to greater water contamination?.

Failing to conserve water can contribute to greater water contamination because when water is wasted or used excessively, it can increase the volume of wastewater that needs to be treated and disposed of.

This wastewater may contain harmful contaminants and pollutants, such as chemicals, pathogens , and bacteria.

Additionally, overuse of water can lead to increased runoff, which can carry pollutants from agricultural and urban areas into rivers, lakes, and other water sources.

This can result in water contamination , which can have negative impacts on human health, wildlife, and ecosystems.

Therefore, conserving water is important not only for ensuring a sustainable supply of water but also for protecting water quality and reducing the risk of water contamination.

To learn more about contamination , refer below:

https://brainly.com/question/29851759

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Crop water status analysis from complex agricultural data using umap-based local biplot.

1. Introduction

2. materials and methods, 2.1. biplot fundamentals, 2.2. uniform manifold approximation and projection (umap).

2.3. UMAP-Based Local Biplot

2.4. tested datasets, 2.4.1. multivariate gaussians, 2.4.2. forage grasses, 2.4.3. riceclimaremote, 3. experiments and results, 3.1. training details, assessment, and method comparison, 3.2. multivariate gaussians results, 3.3. forage grasses dataset results, 3.4. riceclimaremote dataset results, 4. discussion, 5. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Triana-Martinez, J.C.; Álvarez-Meza, A.M.; Gil-González, J.; De Swaef, T.; Fernandez-Gallego, J.A. Crop Water Status Analysis from Complex Agricultural Data Using UMAP-Based Local Biplot. Remote Sens. 2024 , 16 , 2854. https://doi.org/10.3390/rs16152854

Triana-Martinez JC, Álvarez-Meza AM, Gil-González J, De Swaef T, Fernandez-Gallego JA. Crop Water Status Analysis from Complex Agricultural Data Using UMAP-Based Local Biplot. Remote Sensing . 2024; 16(15):2854. https://doi.org/10.3390/rs16152854

Triana-Martinez, Jenniffer Carolina, Andrés Marino Álvarez-Meza, Julian Gil-González, Tom De Swaef, and Jose A. Fernandez-Gallego. 2024. "Crop Water Status Analysis from Complex Agricultural Data Using UMAP-Based Local Biplot" Remote Sensing 16, no. 15: 2854. https://doi.org/10.3390/rs16152854

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