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Statistics Hypothesis For Comparing Performance Ratings By Gender

Statistics Hypothesis For Comparing Performance Ratings By Gender

Question Description

1. What is the null hypothesis for comparing performance ratings by gender?

2. Run a t-test on the data in the spreadsheet. Use a two-tailed, two sample equal variance test. What is the t-value? Round to three decimal points (e.g. 0.351)

3. Is there a significant difference in performance ratings by gender?

a. Yes b. No

4. What is the null hypothesis for determining if there is a relationship between Job Level and Performance Ratings?

5. Run an analysis to determine if there is a correlation between Job Level and Performance Rating. What is the correlation co-efficient? Round to two decimal points (e.g. 0.04)

6. What is the t-value for this relationship? Round to two decimal points (e.g. 0.04)

To answer this question, you have to covert the correlation co-efficient to a t value, using the following formula:

r= the correlation co-efficient

n= the number of observations

7. Is the relationship between Job Level and Performance Ratings significant?

To answer this question, you can convert the t-value to a p-value in excel using the following command.

=t.dist.2t(t, degrees of freedom)

t.dist.2t is the command in excel for a two-tailed Student’s T output

The t in the parenthesis is the value you calculated above (if this is negative, covert it to a positive number by multiplying it by -1)

The degrees of freedom = (number of observations – 2)

If the value you find is less than 0.05, then the relationship is significant.

a. no b. yes