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# Please statistically compare the mean level of satisfaction with base pay between males and females.

INSTRUCTIONS TO CANDIDATES

This data set contains 2 different measures of job satisfaction. Satisfaction with (a) the job itself, and (b) base pay, both measured on a 7-point scale from 1=not at all satisfied to 7=extremely satisfied.  Three groups of employees were assessed (a) unionized workers, (b) lower and middle level managers, and (c) company executives.  Employees were coded based upon sex and country.

1. Please statistically compare the mean level of satisfaction with base pay between males and females. Note it was hypothesized that males would score higher because of perceptions of systematic pay discrimination against women.   This is what you should provide in order (please use labels 1a, 1b, 1ca 1d to organize your response):

1a. Report the t value, degrees of freedom, p-value, and whether or not you would declare statistical significance.  Use the format:  t(df) = x, p< XX.  (3 points)

1b. Report the 95% confidence interval (report the values) for this analysis and explain what the interval means (3 points)

1c. Report Cohen’s d and Eta Squared for this t-test whether the test is statistically significant or not.  (2 points)

1d. What conclusion might you draw from the results of the Levene’s test?  (2 points).

2. 2. Perform a 2 (Country) X 2 (sex) ANOVA with satisfaction with the job as the criterion variable.   Assume there is no violation of the homogeneity of variance assumption. This is what you should provide in order (please use labels 2a, 2b  to organize your overall response):

2a. Report the F-test for the interaction and the Eta Squared (not partial eta squared) estimate of effect size.  Use the Format F(df1, df2) = x, p=xx, Eta Squared = xxx. (2 points).

2b. Treating “Country” as the moderator, perform simple effect tests comparing males and females.  Note there is an expectation that males would be more satisfied compared to females. What alpha level (Type I error) did you use for each simple test? Report the t values using the format:  t(df) = x, p= XX.  For any statistically significant t-test result report Eta Squared as your effect size estimate (8 points).

3. Create 3 age groups 22-35, 36-49, 50 and above.  Run 2 orthogonal planned comparisons with the 3 age groups as a predictor of satisfaction with pay.  Report the pertinent output by copying it into your exam. There is no need to explain the output.  How do the results of these planned comparisons relate to the overall 1-way ANOVA comparing the 3 age groups on the pay satisfaction variable?

4.  What is meant by an error/degrees of freedom trade-off when we consider running a 2-way ANOVA instead of a 1-way ANOVA with a given set of data?  Does the trade-off necessarily work out in our favour such that the same main effect becomes statistically significant only in the 2-way analysis? Why or why not?

5. Assume researchers conducted a repeated-measures ANOVA on an expanded version of the data set for questions 1-2.  They compared the ratings across three types of job satisfaction (the two types of satisfaction from the data set for questions 1-2) as well as a measure of satisfaction with employee benefits (not included in the data set) . Here is a selection of their output:

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