Topic: Sleep’s relationship to other variables (academics, mood, illness, personality)
Statistical Concepts Covered: In this applet, you’ll explore correlational data – data that show a relationship between two variables, but which cannot be used to make claims about causation. You will also think about the potential drawbacks of collecting data by asking individuals survey questions about their habits.
Introduction:
In Chapter 5 you read about the debate surrounding how much sleep you need. While you might think that you can function well on less sleep, studies show that there is a solid relationship between sleeping and learning and memory. In this activity, you will analyze data from the National Longitudinal Study of Adolescent Health, which measured adolescents on a wide range of variables including sleep habits and emotional and academic well-being. Nearly 5000 individuals were measured for the study, and you will analyze representative data from 500 of them to draw conclusions about how sleep (or lack thereof) can affect academic and social variables.
Statistical Lesson. It is important, when interpreting graphs that show frequency data, to think about the base rates: the underlying frequency of an event regardless of a secondary variable that you are studying. In this example, because most students report getting 7 or 8 hours of sleep per night, it shouldn’t be surprising that the number of students who earn As is higher in those categories. Looking at the data as percentages, comparing what portion of all 8-hour sleepers earned As compared to what portion of all 10-hour sleepers earned As, can provide a less biased view of the underlying relationship.
Congratulations! You have completed this activity.