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How does understanding the correlation between variables help us understand regression?

What is the effect of each statistically significant variable?

 

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1.What are the conventional levels of significance set by most researchers? What do these values mean (i.e., p values of .05 and .01)?

 

2.If the result of Z-test reveals that the sample and population are different, what does this tell us about the null hypothesis? What does this suggest about the sample?

 

3.When would it be appropriate to use a t test for independent samples? What is the key piece of information you must know in order to decide?

 

4.What does homogeneity of variance mean? How can it affect your results?

 

5.When would it be appropriate to use a t test of dependent samples? How is this test different from the t test of independent samples?

 

6.What is the test statistic associated with ANOVA? How is this test statistic similar to the t value?

 

7.What if you have more than two groups and you want to see if differences exist among the means of those groups? What is the appropriate statistical analysis?

 

8.What is an interaction effect? Where interaction effects would be found within the source table? How should they be interpreted?

 

9.How do you interpret a p value associated with a correlation coefficient?

 

10.How does understanding the correlation between variables help us understand regression?

 

Excel data analysis questions (50 pts, 5pts each)

Attached please find an Excel survey data file of 1994 Office of Personnel Management (OPM94), with variable names and definition. Please use the dataset to answer the following questions. When possible, please insert Excel outputs in your answers.

 

1.Test whether the mean salary for all federal employees is $36,050 at α=0.05.Please specify the null and alternative hypotheses and explain your finding.

 

2.Test whether the mean salary for all female federal employees is $29,000 at α=0.05.Please specify the null and alternative hypotheses and explain your finding.

 

3.Test the difference between male and female employees’ average salaries. Are the means different? Please construct a 95% confidence interval for the difference and explain your finding.

 

4.Test whether the average salaries are the same among races. Please explain your finding.

 

5.If assuming salary depends on gender, minority, years of education, and years of federal service, please run the regression and provide the regression equation with estimated coefficients. And please use this regression equation for question 7-10.

 

6.Find the coefficient of determination, R2. How fit is the regression model?

 

7.Which regression coefficient(s)is statistically significant? What is the effect of each statistically significant variable?

 

8.What is the expected salary of a female white employee with 16 years of education and federal experience? Please show the calculation.

 

9.Are there any other variables that could be included? Please test 1-2 additional variables listed in the dataset and explain your finding.

 

Download (XLS, 28KB)

 

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