Question

. Exercises 10,22, and 24 describe an experiment investigating the effectiveness of exercise in combating insomnia. Suppose some of the 40 subjects had maintained a healthy weight, but others were quite overweight. Why might researchers choose to block the subjects by weight level before randomly assigning some of each group to the exercise program?

Short answer

Blocking by weight minimizes the confounding effect of weight on the study outcomes, ensuring more accurate results.

Step-by-step solution

Understanding Blocking

Blocking in experiments is a method used to control for variables that could affect the outcome but are not the primary focus of the experiment. In this case, the variable is weight level.

Identifying the Variable

In this experiment, the subjects are divided into those who have a healthy weight and those who are overweight. Weight level is identified as a potential confounding variable that could influence the effectiveness of the exercise program on insomnia.

Purpose of Blocking by Weight Level

Blocking by weight level helps ensure that any differences in the results are likely due to the exercise program itself rather than differences in weight-related factors. By grouping subjects with similar weight levels, the effect of weight on insomnia is minimized.

Ensuring Balanced Groups

After blocking by weight level, subjects within each block are randomly assigned to either the exercise program or a control group. This ensures that each treatment group is balanced in terms of the weight level of the subjects, providing a more accurate measure of the effect of the exercise program.

Key concepts

Confounding Variables

Confounding variables are those sneaky factors that can influence the outcome of an experiment, but they're not the direct focus of what's being studied. Imagine you're trying to find out if exercise helps with insomnia. If some of your participants are of different weight levels, this can mix up the results. This is because their weight might affect their sleep, not just their exercise habits.
By recognizing weight level as a confounding variable, researchers can then use this information to make sure that the results of the study truly reflect the impact of exercise and not the differences in weight. This insight helps ensure the integrity of the experiment's conclusions, making it clearer whether or not exercise is effective in aiding sleep.

Random Assignment

Random assignment is like a random draw where each participant has an equal chance of ending up in any group. This is an important step in designing a study because it ensures that each group is balanced and that each group is similar from the start.
For instance, after blocking participants by weight, the experiment randomly assigns them to either the exercise group or the control group. This helps to prevent any hidden factors from skewing the results. Imagine everyone with a healthy weight ending up in one group; this would make it unfair. Random assignment helps maintain fairness and accuracy by evenly distributing characteristics across both groups.

Experimental Design

Experimental design is like the blueprint for conducting an experiment. It outlines how to handle different variables and how to ensure the results are valid. A well-thought-out design allows researchers to ask specific questions and get specific answers without being tripped up by unrelated factors.
In the insomnia study, blocking participants by weight and then randomly assigning them to groups is a key part of the experimental design. It allows researchers to focus on the effect of exercise on sleep by controlling for weight. This type of design helps researchers make more precise conclusions about the relationship between exercise and insomnia, thus maximizing the reliability and validity of their findings.

• Blocking makes sure that distinct differences, like weight, are addressed so they don't blur the results.
• Random assignment within blocks balances the groups, ensuring results aren’t swayed by outside variables.
• Combining these strategies ensures that the experimental design accurately tests the hypothesis in a controlled manner.