Run the appropriate two way ANOVA analysis and interpret your results. Be sure to evaluate how well the data meet the required assumptions.

Statistics Homework With SPSS
Paper , Order, or Assignment Requirements

Problem 1
Use the Salary data set complete the following problem:
You are interested in seeing whether salary (variable: salary) is related to gender and/or cultural identity. Variables: sex and minority.
a) What are the hypotheses you are considering? There are a number to be examined.
b) Run the appropriate two way ANOVA analysis and interpret your results. Be sure to evaluate how well the data meet the required assumptions. To run this analysis: Analyze>General Linear Model>Univariate placing current salary in the dependent variable box and the other two variables in the Fixed Factor(s) box.
c) Do you reject or not reject the null hypotheses at a confidence level of 95%?
d) Is there evidence of an interaction between gender and cultural identity? If there is, what does it mean?
Problem 2
Use the Salary data set complete the following problem:
You are interested in creating a predictive model of current salary (variable salnow). Specifically, you want to know if the interval variables employee age, job seniority and education (variables: age, edlevel, time) would comprise a predictive model of current salary. Use multiple linear regression to answer the following questions:
a) Is the overall model predictive of salary? Interpret r2 to support your answer.
b) Which (if any) of the independent variables are statistically significant? What is the evidence for this?
Problem 3
In this problem, we will do a formal test of alleged discrimination using the data from Week 1 (Problem 2). Using the California data set, conduct a two factor ANOVA test of impact of ethnicity, age cohort and their interaction on mean expenditure payments. Do you find any evidence of ethnic discrimination?
Problem 4
Use the 04cars data set. You are interested in creating a predictive model of highway miles per gallons.

(a) What variables would you consider as potential independent variables?
(b) What is the correlation between highway miles per gallon and your choice of independent variables?
(c) Estimate a multiple regression model explaining highway miles per gallon using your independent variables.
(d) Is the overall model predictive of highway miles per gallon? Interpret r2 to support your answer.
(e) Which (if any) of the independent variables are statistically significant? What is the evidence for this?

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