BUS 308 Week 5 Problem Set
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ASSIGNMENT WEEK 5 1. Create a correlation table for the variables in our (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 the table here. c. Using r= approximately .28 as the significant
r value (at p = .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 information help us answer our
equal pay for equal work question? 2. Below is a regression analysis for salary being
predicted/explained by the other variables in our sample (Midpoint, age, performance
rating, service, raise, and degree variables). Note: since salary and compa are different
ways of expressing an employee’s salary, we do not want to have both used in the same
regression. Please interpret the findings. 3. Perform a regression analysis using compa as
the dependent variable and the same independent variables as used in question 2. Show
the result, and interpret your findings by answering the same questions. Note: be sure to
include the appropriate hypothesis statements. 4. Based on all of your results to date, is
gender a factor in the pay practices of this company? If so, which gender gets paid more?
How do we know? Which is the best variable to use in analyzing pay practices - salary or
compa? Why? What is the most interesting or surprising thing about the results we got
doing the analyses during the last 5 weeks? 5. Why did the single factor tests and analysis
(such as t and single factor ANOVA tests on salary equality) not provide a complete
answer to our salary equality question? What outcomes in your life or work might benefit
from a multiple regression examination rather than a simpler one variable test?