Types of Variables > Control Variable An experiment has several types of variables, including a
control variable (sometimes called a controlled variable). Variables are just values that can change; a good experiment only has two changing variables: the independent variable and dependent variable. Let’s say you are testing to
see how the amount of light received affects plant growth: If control variables aren’t kept constant, they could ruin your
experiment. For example, you may conclude that plants grow optimally at 4 hours of light a day. However, if your plants are receiving different fertilizer levels, your experiment becomes invalid. As a researcher, you should identify any variables that may affect the outcome of your experiment and you must take steps to keep them constant (“control” them). If you do not, your experiment compromises internal validity,
which is just another way of saying your experimental results will not be valid. When control variables run amok and aren’t controlled, they turn into confounding variables, which affect your results and ruin your experiment. In any experiment or research, it can be virtually impossible to account for all variables that may affect the outcome of your
experiment. If it’s difficult to identify and control all potential confounding variables, it may be necessary to make a control group. A control group provides a baseline measurement for your experiment. ---------------------------------------------------------------------------
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Chegg Study, you can get step-by-step solutions to your questions from an expert in the field. Your first 30 minutes with a Chegg tutor is free! Comments? Need to post a correction? Please Contact Us. Human In each situation, The process of Table 2.3 showed Table 3.1 is
Since this is a Next, we are
than males, and liberals are more likely to say they would vote for a woman. So we introduce liberalism/conservatism as a control variable in our analysis. If females are more likely to support a woman because they are more liberal, then the difference between the preferences of men and women should disappear or be substantially reduced when liberalism/conservatism is held constant. This process is called interpretation because we are interpreting how one variable is related to another variable. Table 3.3 shows what we would expect to find if females supported the woman because they were more liberal. Notice that in both partial tables, the differences in the percentages between men and women has disappeared. (It is not necessary that it disappears entirely, but only that it is substantially reduced in each of the partial tables.)
Finally, let's focus on the third of the situations outlined at the beginning of this section--whether the relationship is the same for different types of individuals. Perhaps the relationship between sex and voter preference varies with other characteristics of the individuals. Maybe among whites, females are more likely to prefer women candidates than the males are, but among blacks, there is little difference between males and females in terms of voter preference. This is the outcome shown in Table 3.4. This process is called specification because it specifies the conditions under which the relationship between sex and voter preference varies. In the earlier
Another point to keep in mind is that chi square is affected by the number of cases in the table. With a lot of cases it is easy to reject the null hypothesis of no relationship. With a few cases, it can be quite hard to reject the null hypothesis. Also, consider the percentages within the table. Look for patterns. Do not rely on any single piece of information. Look at the whole picture. We have concentrated REFERENCES AND Methods of
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What is an example of a control variable?In an experiment to observe the growth of a plant, the temperature can be classified as a control variable if it is controlled during an experiment. Other examples of control variables could be the amount of light, duration of the experiment, amount of water, and pot of the plant.
What are control variables in quantitative research?In quantitative models, a control variable is the one that allows you to isolate the selection bias in a certain observation group. This aims to your statistical inferences are controlled by certain variables that could absorb the explicability of your model, or in other words, increase your error.
What are control variables in a research?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 aims, but is controlled because it could influence the outcomes.
What are some examples of independent and dependent variables and control?Example: a car going down different surfaces. Independent variable: the surface of the slope rug, bubble wrap and wood. Dependent variable: the time it takes for the car to go down the slope. Controlled variable: the height of the slope, the car, the unit of time e.g. minutes and the length of the slope.
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