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multiple regression

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5. HR Assistant Survey
A sample of HR assistants in Plano Texas was created. It was suggested that the data should be analyzed with a regression model to determine if salary was related to years of experience, aptitude test scores, EI (emotional intelligence)scores, number of foreign languages spoken, word processing speed and employee satisfaction. This data is shown in Table 1. Sorry the units of y are difficult to read ($000).

a. Using a correlation matrix determine what variables you might flag going into the initial model. Explain your choices.
b. Determine an initial regression model including all variables. Discuss your adjusted coefficient of determination. Use in a clear easy to understand sentence.
c. Check you significance levels and residuals. Clean up your model based on these results. Explain your step by step results with analytical reasons.
d. Forecast a salary for an applicant with 7 years of experience, an EI score of 50, aptitude score of 82, speed of 25, satisfaction score of 10, languages is 6. Just use those x’s you have determined should be in your final model, do not go back to the original model before cleanup. How comfortable are you with this prediction?

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