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The explanatory variable in any study helps us understand what factors might be affecting the outcome. In the context of the study examining the effect of exercise on body composition, the explanatory variable is the level of physical activity. This is often referred to as the independent variable because it is assumed to influence or bring about a change in the response variable.

For this particular study, women were classified as either active or sedentary based on their weekly hours of physical activity. It is important to remember that in scientific studies, the terms active and sedentary are categories that can help researchers analyze data. Other examples of explanatory variables include temperature in a climate study or dosage of medication in a medical trial. Each serves to see how modifying or observing these factors might affect the study outcome.

The response variable is the focus of the study's outcome. It's what researchers are trying to observe some change in based on the explanatory variable. Often referred to as the dependent variable, its changes are being measured to see the effects of changes in the explanatory variable.

In this specific study, the response variable is the percent body fat of women aged 35 to 50 years. Researchers were interested in seeing if there was any difference in body fat percentage between women who were active versus those who were sedentary. The response variable provides the primary data that will be critically analyzed to answer the research question. This helps in forming conclusions, such as whether an increase in physical activity is associated with a decrease in body fat percentage.

Understanding the difference between correlation and causation is crucial in interpreting study results. Correlation refers to a relationship between two variables, where changes in one variable may accompany changes in another. However, this does not mean one causes the other.

In the study about body fat percentage and activity level, there is a clear correlation: active women tend to have different (lower) body fat percentages compared to sedentary women. However, it is vital to note that this does not establish causation. Other factors, like diet or genetics, could also influence body fat.

Causation implies that a change in one variable actually brings about a change in another. To determine causation, more controlled methods such as experiments where variables are manipulated under controlled conditions are typically used. As this study does not control for all other potential variables, it is classified as observational, meaning while it identifies correlation, it does not confirm causation.