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Chapter 13: Problem 22

Exercise 10 describes an experiment showing that exercise helped people sleep better. The experiment involved other groups of subjects who didn't exercise. Why didn't the experimenters just have everyone exercise and see if their ability to sleep improved?

Short Answer

Expert verified
Control and variable comparison are necessary to determine if exercise affects sleep.

Step by step solution

01

Understand the Purpose of a Control Group

In scientific experiments, a control group is essential to determine the effect of the variable being tested鈥攊n this case, exercise. If everyone in the study exercised, there would be no baseline to compare the results of the sleeping patterns. This control group, which does not exercise, helps identify whether the changes in sleep patterns can be attributed specifically to exercise rather than other factors.
02

Importance of Variable Comparison

By having some participants exercise and others not, the researchers can compare the results between the two groups. This comparison allows them to isolate the effect of exercise on sleep quality. If only the experiment group improved in sleep patterns, researchers have stronger evidence that exercise is the cause.
03

Avoid Confounding Variables

In experiments, it's important to minimize confounding variables鈥攆actors other than the independent variable (exercise) that might influence the outcome (sleep quality). Having a non-exercising group helps control for those variables, providing clearer insight into cause-and-effect relationships.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Scientific Experiment
In a scientific experiment, researchers aim to discover the effects of a particular variable on a specific outcome. They achieve this through structured and controlled testing. When scientists design an experiment, they set up conditions to thoroughly investigate how a variable influences the results they are studying.
This process often involves multiple elements:
  • Hypothesis: A prediction about the relationship between variables.
  • Independent Variable: The variable that is changed or controlled to test its effects鈥攍ike exercise in our example.
  • Dependent Variable: The outcome being measured, such as sleep quality in this scenario.
By maintaining consistency in the environment and using a control group, scientists can focus solely on the changes brought about by the variable they are testing.
Variable Comparison
The comparison between different groups is fundamental in determining the effectiveness of the independent variable. In the context of the exercise and sleep experiment, researchers compared two groups to draw conclusions about causation.
The two key groups in this study were:
  • Experimental Group: Participants who exercised regularly.
  • Control Group: Participants who did not exercise.
This setup allows researchers to observe differences in sleep quality between those who exercise and those who do not. If the sleeping patterns improved only in those who exercised, it provides strong evidence that exercise plays a significant role. Without comparing these distinct groups, it would be challenging to assert that exercise alone contributed to better sleep.
Confounding Variables
Confounding variables pose significant challenges in scientific studies, as they introduce alternative explanations for outcomes. These are factors other than the one being studied that might influence the study's results. In the exercise and sleep study, it's key to control for these variables to establish a clear cause-and-effect relationship.
To manage confounding variables, researchers can:
  • Randomize Participants: Randomly assigning subjects to groups helps ensure that potential confounders are equally distributed.
  • Standardize Conditions: Keeping the environment consistent minimizes the influence of external factors.
  • Include Control Groups: A control group that does not receive the treatment (exercise) helps attribute observed effects more directly to the independent variable alone.
By applying these strategies, researchers strengthen the validity of their findings, offering more reliable evidence on the effects of the variables they are interested in.

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Most popular questions from this chapter

Coffee stations in offices often just ask users to leave money in a tray to pay for their coffee, but many people cheat. Researchers at Newcastle University replaced the picture of flowers on the wall behind the coffee station with a picture of staring eyes. They found that the average contribution increased significantly above the well-established standard when people felt they were being watched, even though the eyes were patently not real. (NY Times \(12 / 10 / 06)\) a) Was this a survey, an observational study, or an experiment? How can we tell? b) Identify the variables. c) What does "increased significantly" mean in a statistical sense? 7-20. What's the design? Read each brief report of statistical research, and identify a) whether it was an observational study or an experiment. If it was an observational study, identify (if possible) b) whether it was retrospective or prospective. c) the subjects studied and how they were selected.

describes an experiment that showed that high doses of omega-3 fats might be of benefit to people with bipolar disorder. The experiment involved a control group of subjects who received a placebo. Why didn't the experimenters just give everyone the omega-3 fats to see if they improved?

A running-shoe manufacturer wants to test the effect of its new sprinting shoe on 100 -meter dash times. The company sponsors 5 athletes who are running the 100 -meter dash in the 2004 Summer Olympic games. To test the shoe, it has all 5 runners run the 100 -meter dash with a competitor's shoe and then again with their new shoe. The company uses the difference in times as the response variable. a) Suggest some improvements to the design. b) Why might the shoe manufacturer not be able to generalize the results they find to all runners?

An experiment that showed that subjects fed the DASH diet were able to lower their blood pressure by an average of \(6.7\) points compared to a group fed a "control diet." All meals were prepared by dieticians. a) Why were the subjects randomly assigned to the diets instead of letting people pick what they wanted to eat? b) Why were the meals prepared by dieticians? c) Why did the researchers need the control group? If the DASH diet group's blood pressure was lower at the end of the experiment than at the beginning, wouldn't that prove the effectiveness of that diet? d) What additional information would you want to know in order to decide whether an average reduction in blood pressure of \(6.7\) points was statistically significant?

When spending large amounts to purchase advertising time, companies want to know what audience they'll reach. In January \(2007, \mathrm{a}\) poll asked 1008 American adults whether they planned to watch the upcoming Super Bowl. Men and women were asked separately whether they were looking forward more to the football game or to watching the commercials. Among the men, \(16 \%\) were planning to watch and were looking forward primarily to the commercials. Among women, \(30 \%\) were looking forward primarily to the commercials. a) Was this a stratified sample or a blocked experiment? Explain. b) Was the design of the study appropriate for the advertisers' questions?
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