Dr.Tabor wanted to investigate the relationship between sleep and levels of alertness. She gave surveys to 150 college freshmen in her introduction to psychology course, asking them to report how many hours they slept each night during a 2- week period. Each day at the end of class, Dr. Tabor also had the participants rate their level of alertness on a scale of 1 to 10, with 10 being the most alert. Dr.Tabor compared the average amount of sleep reported by each participant along with their average score on the alertness scale on a graph to examine the data. The resulting correlation coefficient for Dr.Tabor's data was +0.89. Explain how each of the following concepts might apply to Dr.Tabor's research. • Random sample • Scatterplot • Working effects • Positive correlation • Operational definition
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-If Dr. Tabor wishes to study the relationship between sleep and alertness in the general population, she has failed to use a random sample. Her sample is exclusively drawn from college freshman. This nonrandom sample introduces the possibility of confounding variables causing the correlation. For instance, perhaps freshman have not adjusted to the academic and social demands of college and are therefore more vulnerable to the negative effects of sleep deprivation whereas older students have learned how to cope with sleep deprivation.
-Dr. Tabor could use a scatterplot to visually represent her data, charting average hours of sleep on the X-axis and average alertness levels on the Y-axis. Since the data is strongly positively correlated, the scatterplot would show values rising from the bottom-left corner toward the upper-right corner.
-Dr. Tabor would have to be careful not to bias student responses to her survey through wording effects. If, for example, she asked students to rate “how tired or alert you feel after last night’s sleep,” she would be cuing students to think about how they should feel based upon their sleep rather than how they actually feel.
-The results of Dr. Tabor’s survey show a strong positive correlation (+0.89) between hours of sleep and alertness levels. This does not mean, however, that longer sleep causes higher alertness levels. A third variable could be at play (e.g. both a lack of sleep and poor alertness are caused by partying the night before).
-Dr. Tabor gives an operational definition to alertness by having students rate it on a scale from 1 (not at all alert) to 10 (very alert). This may not be the best way to operationally define alertness, since some students may not be the best judges of their own alertness levels. Still this method could easily be replicated by future researchers. She should also give a precise operational definition to hours of sleep (e.g. hours of restful sleep, excluding time in bed spent staring at screens or tossing and turning).
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