Confidence Intervals and Chi Square

BUS 308 Week 4 Assignment in EXCEL (Latest Data, A+ Grade Guaranteed)

 

Week 4

Confidence Intervals and Chi Square

 

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)?

 

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?

Can the means be equal?  Yes/No  Why?

 

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?

 

3. We found last week that the degrees compa 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 the same distribution of degrees by grade?

 

 

What are the hypothesis statements:

Ho:

Ha:

 

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?

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:

 

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:

 

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?

If you rejected the null, what is the Phi correlation:

What does this correlation mean?

 

5. How do you interpret these results in light of our question about equal pay for equal work?

 

 

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