week 5 bus308

Score: Week 5  Correlation and Regression

<1 point> 1.     Create a correlation table for the variables in our data set. (Use analysis ToolPak or StatPlus:mac LE function Correlation.)
a.  Reviewing the data levels from week 1, what variables can be used in a Pearson’s Correlation table (which is what Excel produces)?

b. Place table here (C8):

c. Using r = approximately .28 as the signicant r value (at p = 0.05) for a correlation between 50 values, what variables are
significantly related to Salary?
To compa?

d. Looking at the above correlations – both significant or not – are there any surprises -by that I
mean any relationships you expected to be meaningful and are not and vice-versa?

e. Does this help us answer our equal pay for equal work question?

<1 point> 2   Below is a regression analysis for salary being predicted/explained by the other variables in our sample  (Midpoint,
age, performance rating, service,  gender, and degree variables. (Note: since salary and compa are different ways of
expressing an employeeâ€™s salary, we do not want to have both used in the same regression.)
Plase interpret the findings.

Ho: The regression equation is not significant.
Ha: The regression equation is significant.
Ho: The regression coefficient for each variable is not significant   Note: technically we have one for each input variable.
Ha: The regression coefficient for each variable is significant   Listing it this way to save space.

Sal
SUMMARY OUTPUT

Regression Statistics
Multiple R 0.9915591
R Square 0.9831894  