Week 4 BUS 308 Solution
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| 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 | F | ||||||
| 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? | ||||||||||||||||
11 years ago
Week 4 BUS 308 Solution
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