Elaborating Bivariate Tables

1. Controlling for a third variable

Suppose a researcher conducts a study to analyze the relationship between an individual's amount of yearly vacation time and that individual's stress level. For this study, the researcher has decided to focus on stress levels of single men. From a sample of 70 single men, the researcher collects information from all the subjects about their stress levels (Y) and how much time they spend on vacation every year. Vacation time (X) is reported as low if an individual spends 7 or fewer days per year on vacation and high if more than 7 days per year.

The researcher suspects that people who spend more time on vacation will report higher stress levels. The actual data from the study are displayed in the following table.

	Stress Level (Y)
Vacation Time (X)	Low	High	Totals
Low	17 (68.0%)	36 (80.0%)	53
High	8 (32.0%)	9 (20.0%)	17
Totals	25 (100.0%)	45 (100.0%)	70
	Gamma = -0.3061

The data in the table show _____________ (a. no, b. a perfect, c. a negative or d. a positive) association between these variables. This __________ (a.proves, b. ignores, c. supports or d. contradicts) the researcher's original hypothesis that people who spend more time on vacation will report higher stress levels.

If increased vacation time was the sole cause of decreasing an individual's stress level, then you would see a gamma = ______ (a. 0, b. +1, c. -1, or d. +0.3061). Therefore, you can assume that _________ (a.other variables, or b. no other variables) are affecting the relationship.

Which of the following factors might also be influencing the relationship?Check all that apply.

Work schedule

Height

Health status

No other factors

Shoe size

Income level