BUS308 – WEEK 4
| Score: | Week 4 | Confidence Intervals and Chi Square (Chs 11 – 12) | |||||||||||||
| For questions 3 and 4 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 point> | 1 | Using our sample data, construct a 95% confidence interval for the population’s mean salary for each gender. | |||||||||||||
| Interpret the results. How do they compare with the findings in the week 2 one sample t-test outcomes (Question 1)? | |||||||||||||||
| Mean | St error | t value | Low | to | High | ||||||||||
| Males | |||||||||||||||
| Females | |||||||||||||||
| <Reminder: standard error is the sample standard deviation divided by the square root of the sample size.> | |||||||||||||||
| Interpretation: | |||||||||||||||
| <1 point> | 2 | Using our sample data, construct a 95% confidence interval for the mean salary difference between the genders in the population. | |||||||||||||
| How does this compare to the findings in week 2, question 2? | |||||||||||||||
| Difference | St Err. | T value | Low | to | High | ||||||||||
| Yes/No | |||||||||||||||
| Can the means be equal? | Why? | ||||||||||||||
| How does this compare to the week 2, question 2 result (2 sampe t-test)? | |||||||||||||||
| a. | Why is using a two sample tool (t-test, confidence interval) a better choice than using 2 one-sample techniques when comparing two samples? | ||||||||||||||
| <1 point> | 3 | We found last week that the degree values within the population do not impact compa rates. | |||||||||||||
| This does not mean that degrees are distributed evenly across the grades and genders. | |||||||||||||||
| Do males and females have athe same distribution of degrees by grade? | |||||||||||||||
| (Note: while technically the sample size might not be large enough to perform this test, ignore this limitation for this exercise.) | |||||||||||||||
| What are the hypothesis statements: | |||||||||||||||
| Ho: | |||||||||||||||
| Ha: | |||||||||||||||
| Note: You can either use the Excel Chi-related functions or do the calculations manually. | |||||||||||||||
| Data input tables – graduate degrees by gender and grade level | |||||||||||||||
| OBSERVED | A | B | C | D | E | F | Total | If desired, you can do manual calculations per cell here. | |||||||
| M Grad | A | B | C | D | E | F | |||||||||
| Fem Grad | M Grad | ||||||||||||||
| Male Und | Fem Grad | ||||||||||||||
| Female Und | Male Und | ||||||||||||||
| Female Und | |||||||||||||||
| Sum = | |||||||||||||||
| EXPECTED | |||||||||||||||
| M Grad | For this exercise – ignore the requirement for a correction factor | ||||||||||||||
| Fem Grad | for cells with expected values less than 5. | ||||||||||||||
| Male Und | |||||||||||||||
| Female Und | |||||||||||||||
| Interpretation: | |||||||||||||||
| What is the value of the chi square statistic: | |||||||||||||||
| What is the p-value associated with this value: | |||||||||||||||
| Is the p-value <0.05? | |||||||||||||||
| Do you reject or not reject the null hypothesis: | |||||||||||||||
| If you rejected the null, what is the Cramer’s V correlation: | |||||||||||||||
| What does this correlation mean? | |||||||||||||||
| What does this decision mean for our equal pay question: | |||||||||||||||
| <1 point> | 4 | Based on our sample data, can we conclude that males and females are distributed across grades in a similar pattern | |||||||||||||
| within the population? | |||||||||||||||
| What are the hypothesis statements: | |||||||||||||||
| Ho: | |||||||||||||||
| Ha: | |||||||||||||||
| Do manual calculations per cell here (if desired) | |||||||||||||||
| A | B | C | D | E | F | A | B | C | D | E | |||||
| OBS COUNT – m | M | ||||||||||||||
| OBS COUNT – f | F | ||||||||||||||
| Sum = | |||||||||||||||
| EXPECTED | |||||||||||||||
| What is the value of the chi square statistic: | |||||||||||||||
| What is the p-value associated with this value: | |||||||||||||||
| Is the p-value <0.05? | |||||||||||||||
| Do you reject or not reject the null hypothesis: | |||||||||||||||
| If you rejected the null, what is the Phi correlation: | |||||||||||||||
| What does this correlation mean? | |||||||||||||||
| What does this decision mean for our equal pay question: | |||||||||||||||
| <2 points> | 5. How do you interpret these results in light of our question about equal pay for equal work? | ||||||||||||||
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