Posted: May 17th, 2021

BUS 308 Week 5 Assignment

Question description

Data Sheet BUS 308.xlsx
Week 5 Correlation and Regression
For
each question involving a statistical test below, list the null and alternate
hypothesis statements.  Use .05 for
your significance level in making your decisions.
For
full credit, you need to also show the statistical outcomes - either the
Excel test result or the calculations you performed.
1
Create a correlation
table for the variables in our data set. (Use analysis ToolPak function
Correlation.)
a. Interpret the
results.  What variables seem to be
important in seeing if we pay males and females equally for equal work?
2
Below is a regression
analysis for salary being predicted/explained by the other variables in our
sample  (Mid,
age, ees, sr, raise, and deg 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.)
Ho: The regression
equation is not significant.
Ha: The regression
equation is significant.
Ho: The regression
coefficient for each variable is not significant
Ha: The regression
coefficient for each variable is significant
Sal
The analysis used Sal as
the y (dependent variable) and
SUMMARY OUTPUT
mid, age, ees, sr, g,
raise, and deg as the dependent
variables (entered as a
range).
Regression
Statistics
Multiple R
0.99215498
R Square
0.9843715
Adjusted R Square
0.98176675
Standard Error
2.59277631
Observations
50
ANOVA
df
SS
MS
F
Significance F
Regression
7
17783.7
2540.52
377.914
8.44043E-36
Residual
42
282.345
6.72249
Total
49
18066
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
-4.009
3.775
-1.062
0.294
-11.627
3.609
-11.627
3.609
Mid
1.220
0.030
40.674
0.000
1.159
1.280
1.159
1.280
Age
0.029
0.067
0.439
0.663
-0.105
0.164
-0.105
0.164
EES
-0.096
0.047
-2.020
0.050
-0.191
0.000
-0.191
0.000
SR
-0.074
0.084
-0.876
0.386
-0.244
0.096
-0.244
0.096
G
2.552
0.847
3.012
0.004
0.842
4.261
0.842
4.261
Raise
0.834
0.643
1.299
0.201
-0.462
2.131
-0.462
2.131
Deg
1.002
0.744
1.347
0.185
-0.500
2.504
-0.500
2.504
Interpretation:
Do you reject or not reject the regression
null hypothesis?
Do you reject or not
reject the null hypothesis for each variable?
What is the regression
equation, using only significant variables if any exist?
What does result tell us
about equal pay for equal work for males and females?
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?  Why or why not?
Which is the best
variable to use in analyzing pay practices - salary or compa?  Why?
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?

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