| Score: | Week 3 | ANOVA and Paired T-test |
| | At this point we know the following about male and female salaries. |
| | a. | Male and female overall average salaries are not equal in the population. |
| | b. | Male and female overall average compas are equal in the population, but males are a bit more spread out. |
| | c. | The male and female salary range are almost the same, as is their age and service. |
| | d. | Average performance ratings per gender are equal. |
| | Let's look at some other factors that might influence pay - education(degree) and performance ratings. |
| <1 point> | 1 | Last week, we found that average performance ratings do not differ between males and females in the population. |
| | | Now we need to see if they differ among the grades. Is the average performace rating the same for all grades? |
| | | (Assume variances are equal across the grades for this ANOVA.) | | | | | | | You can use these columns to place grade Perf Ratings if desired. |
| | | | | | | | | | A | B | C | D | E | F |
| | | Null Hypothesis: |
| | | Alt. Hypothesis: |
| | | Place B17 in Outcome range box. |
| | | Interpretation: |
| | | | | | | What is the p-value: |
| | | | | | | Is P-value < 0.05? |
| | | | | | | Do we REJ or Not reject the null? |
| | | If the null hypothesis was rejected, what is the effect size value (eta squared): |
| | | | | | | Meaning of effect size measure: |
| | | | | | | What does that decision mean in terms of our equal pay question: |
| <1 point> | 2 | While it appears that average salaries per each grade differ, we need to test this assumption. |
| | | Is the average salary the same for each of the grade levels? (Assume equal variance, and use the analysis toolpak function ANOVA.) |
| | | Use the input table to the right to list salaries under each grade level. |
| | | Null Hypothesis: | | | | | | | If desired, place salaries per grade in these columns |
| | | Alt. Hypothesis: | | | | | | | A | B | C | D | E | F |
| | | Place B55 in Outcome range box. |
| | | | | | | What is the p-value: |
| | | | | | | Is P-value < 0.05? |
| | | | | | | Do you reject or not reject the null hypothesis: |
| | | If the null hypothesis was rejected, what is the effect size value (eta squared): |
| | | | | | | Meaning of effect size measure: |
| | | | | | | Interpretation: |
| <1 point> | 3 | The table and analysis below demonstrate a 2-way ANOVA with replication. Please interpret the results. |
| | | | BA | MA | | Ho: Average compas by gender are equal |
| | | Male | 1.017 | 1.157 | | Ha: Average compas by gender are not equal |
| | | | 0.870 | 0.979 | | Ho: Average compas are equal for each degree |
| | | | 1.052 | 1.134 | | Ha: Average compas are not equal for each degree |
| | | | 1.175 | 1.149 | | Ho: Interaction is not significant |
| | | | 1.043 | 1.043 | | Ha: Interaction is significant |
| | | | 1.074 | 1.134 |
| | | | 1.020 | 1.000 | | Perform analysis: |
| | | | 0.903 | 1.122 |
| | | | 0.982 | 0.903 | | Anova: Two-Factor With Replication |
| | | | 1.086 | 1.052 |
| | | | 1.075 | 1.140 | | SUMMARY | BA | MA | Total |
| | | | 1.052 | 1.087 | | Male |
| | | Female | 1.096 | 1.050 | | Count | 12 | 12 | 24 |
| | | | 1.025 | 1.161 | | Sum | 12.349 | 12.9 | 25.249 |
| | | | 1.000 | 1.096 | | Average | 1.0290833333 | 1.075 | 1.0520416667 |
| | | | 0.956 | 1.000 | | Variance | 0.006686447 | 0.0065198182 | 0.0068660417 |
| | | | 1.000 | 1.041 |
| | | | 1.043 | 1.043 | | Female |
| | | | 1.043 | 1.119 | | Count | 12 | 12 | 24 |
| | | | 1.210 | 1.043 | | Sum | 12.791 | 12.787 | 25.578 |
| | | | 1.187 | 1.000 | | Average | 1.0659166667 | 1.0655833333 | 1.06575 |
| | | | 1.043 | 0.956 | | Variance | 0.006102447 | 0.0042128106 | 0.004933413 |
| | | | 1.043 | 1.129 |
| | | | 1.145 | 1.149 | | Total |
| | | | | | | Count | 24 | 24 |
| | | | | | | Sum | 25.14 | 25.687 |
| | | | | | | Average | 1.0475 | 1.0702916667 |
| | | | | | | Variance | 0.0064703478 | 0.0051561286 |
| | | | | | | ANOVA |
| | | | | | | Source of Variation | SS | df | MS | F | P-value | F crit |
| | | | | | | Sample | 0.0022550208 | 1 | 0.0022550208 | 0.3834821171 | 0.5389389507 | 4.0617064601 | (This is the row variable or gender.) |
| | | | | | | Columns | 0.0062335208 | 1 | 0.0062335208 | 1.0600539609 | 0.3088295633 | 4.0617064601 | (This is the column variable or Degree.) |
| | | | | | | Interaction | 0.0064171875 | 1 | 0.0064171875 | 1.0912877664 | 0.3018915062 | 4.0617064601 |
| | | | | | | Within | 0.25873675 | 44 | 0.0058803807 |
| | | | | | | Total | 0.2736424792 | 47 |
| | | Interpretation: |
| | For Ho: Average compas by gender are equal | | | | | Ha: Average compas by gender are not equal |
| | | | | | | What is the p-value: |
| | | | | | | Is P-value < 0.05? |
| | | | | | | Do you reject or not reject the null hypothesis: |
| | | If the null hypothesis was rejected, what is the effect size value (eta squared): |
| | | | | | | Meaning of effect size measure: |
| | For Ho: Average compas are equal for all degrees | | | | | Ha: Average compas are not equal for all grades |
| | | | | | | What is the p-value: |
| | | | | | | Is P-value < 0.05? |
| | | | | | | Do you reject or not reject the null hypothesis: |
| | | If the null hypothesis was rejected, what is the effect size value (eta squared): |
| | | | | | | Meaning of effect size measure: |
| | | For: Ho: Interaction is not significant | | | Ha: Interaction is significant |
| | | | | | | What is the p-value: |
| | | | | | | Is P-value < 0.05? |
| | | | | | | Do you reject or not reject the null hypothesis: |
| | | If the null hypothesis was rejected, what is the effect size value (eta squared): |
| | | | | | | Meaning of effect size measure: |
| | | | | | | What do these decisions mean in terms of our equal pay question: |
| | | | | | | | | | | | | | Place data values in these columns |
| <1 point> | 4 | Many companies consider the grade midpoint to be the "market rate" - what is needed to hire a new employee. | | | | | | | | | | | Salary | Midpoint |
| | | Does the company, on average, pay its existing employees at or above the market rate? |
| | | Null Hypothesis: |
| | | Alt. Hypothesis: |
| | | | Statistical test to use: |
| | | Place the cursor in B160 for test. |
| | | | What is the p-value: |
| | | | Is P-value < 0.05? |
| | What else needs to be checked on a 1-tail in order to reject the null? |
| | | | Do we REJ or Not reject the null? |
| | If the null hypothesis was rejected, what is the effect size value: | | | NA |
| | | | Meaning of effect size measure: | NA |
| | | Interpretation: |
| <2 points> | 5. | Using the results up thru this week, what are your conclusions about gender equal pay for equal work at this point? |