| Week 2 | Testing means with the t-test | | | <Note: use right click on row numbers to insert rows to perform analysis below any question> |
| For questions 2 and 3 below, be sure to list the null and alternate hypothesis statements. Use .05 for your significance level in making your decisions. |
| For full credit, you need to also show the statistical outcomes - either the Excel test result or the calculations you performed. |
| 1 | Below are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean. |
| | Based on our sample, how do you interpret the results and what do these results suggest about the population means for male and female salaries? |
| | Males | | | | Females |
| | Ho: Mean salary = 45 | | | | Ho: Mean salary = 45 |
| | Ha: Mean salary =/= 45 | | | | Ha: Mean salary =/= 45 |
| | Note when performing a one sample test with ANOVA, the second variable (Ho) is listed as the same value for every corresponding value in the data set. |
| | t-Test: Two-Sample Assuming Unequal Variances | | | | t-Test: Two-Sample Assuming Unequal Variances |
| | Since the Ho variable has Var = 0, variances are unequal; this test defaults to 1 sample t in this situation |
| | | Male | Ho | | | Female | Ho |
| | Mean | 52 | 45 | | Mean | 38 | 45 |
| | Variance | 316 | 0 | | Variance | 334.6666666667 | 0 |
| | Observations | 25 | 25 | | Observations | 25 | 25 |
| | Hypothesized Mean Difference | 0 | | | Hypothesized Mean Difference | 0 |
| | df | 24 | | | df | 24 |
| | t Stat | 1.9689038266 | | | t Stat | -1.9132063573 |
| | P(T<=t) one-tail | 0.0303078503 | | | P(T<=t) one-tail | 0.0338621184 |
| | t Critical one-tail | 1.7108820799 | | | t Critical one-tail | 1.7108820799 |
| | P(T<=t) two-tail | 0.0606157006 | | | P(T<=t) two-tail | 0.0677242369 |
| | t Critical two-tail | 2.0638985616 | | | t Critical two-tail | 2.0638985616 |
| | Conclusion: Do not reject Ho | | | | Conclusion: Do not reject Ho |
| Interpretation: | (include comments on why the conclusion was made, what the conclusion means about pay levels in English, what the conclusions mean for our question about equal pay.) |
| 2 | Based on our sample results, perform a 2-sample t-test to see if the population male and female salaries could be equal to each other. | | | | | | | | | | | Include hypothesis pair of claims, and intepretation of result |
| 3 | Based on our sample results, can the male and female compas in the population be equal to each other? (Another 2-sample t-test.) | | | | | | | | | | | Include hypothesis pair of claims, and intepretation of result |
| 4 | What other information about our variables would you like to know to answer the question about salary equality between the genders? Why - how do these variables influce pay? |
| 5 | If the salary and compa mean tests in questions 3 and 4 provide different results about male and female salary equality, |
| | which would be more appropriate to use in answering the question about salary equity? Why? |
| | What are your conclusions about the tests performed to determine if equal pay exists between the genders at this point? |