BUS 308 week 3 Assignment
xoonAt this point we know the following about male and female salaries. |
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a. | Male and female overall average salaries are not equal in the population. |
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b. | Male and female overall average compas are equal in the population, but males are a bit more spread out. |
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c. | The male and female salary range are almost the same, as is their age and service. |
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d. | Average performance ratings per gender are equal. |
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Let's look at some other factors that might influence pay - education(degree) and performance ratings. |
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1 | Last week, we found that average performance ratings do not differ between males and females in the population. |
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| Now we need to see if they differ among the grades. Is the average performace rating the same for all grades? |
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| (Assume variances are equal across the grades for this ANOVA.) |
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| Null Hypothesis: |
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| Alt. Hypothesis: |
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| Place B17 in Outcome range box. |
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| Interpretation: |
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| What is the p-value: |
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| Is P-value < 0.05? |
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| Do we REJ or Not reject the null? |
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| If the null hypothesis was rejected, what is the effect size value (eta squared): |
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| Meaning of effect size measure: |
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| What does that decision mean in terms of our equal pay question: |
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2 | While it appears that average salaries per each grade differ, we need to test this assumption. |
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| 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. |
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| Null Hypothesis: |
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| Alt. Hypothesis: |
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| A | B | C | D | E | F |
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| Place B55 in Outcome range box. |
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| What is the p-value: |
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| Is P-value < 0.05? |
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| Do you reject or not reject the null hypothesis: |
If the null hypothesis was rejected, what is the effect size value (eta squared): | ||||
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| Meaning of effect size measure: |
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| Interpretation: |
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3 | The table and analysis below demonstrate a 2-way ANOVA with replication. Please interpret the results. |
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| BA | MA |
| Ho: Average compas by gender are equal |
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| Male | 1.017 | 1.157 |
| Ha: Average compas by gender are not equal |
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| 0.870 | 0.979 |
| Ho: Average compas are equal for each degree |
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| 1.052 | 1.134 |
| Ho: Average compas are not equal for each degree |
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| 1.175 | 1.149 |
| Ho: Interaction is not significant |
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| 1.043 | 1.043 |
| Ha: Interaction is significant |
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| 1.074 | 1.134 |
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| 1.020 | 1.000 |
| Perform analysis: |
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| 0.903 | 1.122 |
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| 0.982 | 0.903 |
| Anova: Two-Factor With Replication |
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| 1.086 | 1.052 |
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| 1.075 | 1.140 |
| SUMMARY | BA | MA | Total |
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| 1.052 | 1.087 |
| Male |
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| Female | 1.096 | 1.050 |
| Count | 12 | 12 | 24 |
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| 1.025 | 1.161 |
| Sum | 12.349 | 12.9 | 25.249 |
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| 1.000 | 1.096 |
| Average | 1.02908333 | 1.075 | 1.052042 |
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| 0.956 | 1.000 |
| Variance | 0.00668645 | 0.00652 | 0.006866 |
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| 1.000 | 1.041 |
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| 1.043 | 1.043 |
| Female |
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| 1.043 | 1.119 |
| Count | 12 | 12 | 24 |
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| 1.210 | 1.043 |
| Sum | 12.791 | 12.787 | 25.578 |
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| 1.187 | 1.000 |
| Average | 1.06591667 | 1.065583 | 1.06575 |
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| 1.043 | 0.956 |
| Variance | 0.00610245 | 0.004213 | 0.004933 |
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| 1.043 | 1.129 |
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| 1.145 | 1.149 |
| Total |
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| Count | 24 | 24 |
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| Sum | 25.14 | 25.687 |
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| Average | 1.0475 | 1.070292 |
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| Variance | 0.00647035 | 0.005156 |
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| ANOVA |
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| Source of Variation | SS | df | MS | F | P-value | F crit |
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| Sample | 0.00225502 | 1 | 0.002255 | 0.383482 | 0.538939 | 4.061706 | (This is the row variable or gender.) | |||
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| Columns | 0.00623352 | 1 | 0.006234 | 1.060054 | 0.30883 | 4.061706 | (This is the column variable or Degree.) | |||
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| Interaction | 0.00641719 | 1 | 0.006417 | 1.091288 | 0.301892 | 4.061706 |
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| Within | 0.25873675 | 44 | 0.00588 |
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| Total | 0.27364248 | 47 |
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| Interpretation: |
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For Ho: Average compas by gender are equal | Ha: Average compas by gender are not equal |
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| What is the p-value: |
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| Is P-value < 0.05? |
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| Do you reject or not reject the null hypothesis: |
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| If the null hypothesis was rejected, what is the effect size value (eta squared): |
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| Meaning of effect size measure: |
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For Ho: Average salaries are equal for all grades | Ha: Average salaries are not equal for all grades |
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| What is the p-value: |
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| Is P-value < 0.05? |
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| Do you reject or not reject the null hypothesis: |
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| If the null hypothesis was rejected, what is the effect size value (eta squared): |
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| Meaning of effect size measure: |
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| For: Ho: Interaction is not significant | Ha: Interaction is significant |
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| What is the p-value: |
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| Do you reject or not reject the null hypothesis: |
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| If the null hypothesis was rejected, what is the effect size value (eta squared): |
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| Meaning of effect size measure: |
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| What do these decisions mean in terms of our equal pay question: |
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4 | Many companies consider the grade midpoint to be the "market rate" - what is needed to hire a new employee. |
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| Midpoint | Salary |
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| Does the company, on average, pay its existing employees at or above the market rate? |
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| Null Hypothesis: |
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| Alt. Hypothesis: |
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| Statistical test to use: |
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| Place the cursor in B160 for correl. |
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| What is the p-value: |
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| Is P-value < 0.05? |
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| Do we REJ or Not reject the null? |
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If the null hypothesis was rejected, what is the effect size value: | Since the effect size was not discussed in this chapter, we do not have a formula for it - it differs from the non-paired t. |
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| Meaning of effect size measure: | NA |
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| Interpretation: |
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5. | Using the results up thru this week, what are your conclusions about gender equal pay for equal work at this point? |
- 9 years ago
Purchase the answer to view it
- solutions_bus_308_week_3.xlsx