The writer is very fast, professional and responded to the review request fast also. Thank you.
Book/movie review
22/08/2022
Week 4: Identifying relationships – correlations and regression
To Ensure full credit for each question, you need to show how you got your results. This involves either showing where the data you used is located
or showing the excel formula in each cell. Be sure to copy the appropriate data columns from the data tab to the right for your use this week.
1 What is the correlation between and among the interval/ratio level variables with salary? (Do not include compa-ratio in this question.)
a. Create the correlation table. Use Cell K08 for the Excel test outcome location.
i. What is the data input ranged used for this question:
ii. Create a correlation table in cell K08.
b. Technically, we should perform a hypothesis testing on each correlation to determine
if it is significant or not. However, we can be faithful to the process and save some
time by finding the minimum correlation that would result in a two tail rejection of the null.
We can then compare each correlation to this value, and those exceeding it (in either a
positive or negative direction) can be considered statistically significant.
i. What is the t-value we would use to cut off the two tails? T =
ii. What is the associated correlation value related to this t-value? r =
c. What variable(s) is(are) significantly correlated to salary?
d. Are there any surprises – correlations you though would be significant and are not, or non significant correlations you thought would be?
e. Why does or does not this information help answer our equal pay question?
2 Perform a regression analysis using salary as the dependent variable and the variables used in Q1 along with
our two dummy variables – gender and education. Show the result, and interpret your findings by answering the following questions.
Suggestion: Add the dummy variables values to the right of the last data columns used for Q1.
What is the multiple regression equation predicting/explaining salary using all of our possible variables except compa-ratio?
a. What is the data input ranged used for this question:
b. Step 1: State the appropriate hypothesis statements: Use Cell M34 for the Excel test outcome location.
Ho:
Ha:
Step 2: Significance (Alpha):
Step 3: Test Statistic and test:
Why this test?
Step 4: Decision rule:
Step 5: Conduct the test – place test function in cell M34
Step 6: Conclusion and Interpretation
What is the p-value:
What is your decision: REJ or NOT reject the null?
Why?
What is your conclusion about the factors influencing the population compa-ratio values?
c. If we rejected the null hypothesis, we need to test the significance of each of the variable coefficients.
Step 1: State the appropriate coefficient hypothesis statements: (Write a single pair, we will use it for each variable separately.)
Ho:
Ha:
Step 2: Significance (Alpha):
Step 3: Test Statistic and test:
Why this test?
Step 4: Decision rule:
Step 5: Conduct the test
Note, in this case the test has been performed and is part of the Regression output above.
Step 6: Conclusion and Interpretation
Place the t and p-values in the following table
Identify your decision on rejecting the null for each variable. If you reject the null, place the coefficient in the table.
Midpoint Age Perf. Rat. Seniority Raise Gender Degree
t-value:
P-value:
Rejection Decision:
If Null is rejected, what is the variable’s coefficient value?
Using the intercept coefficient and only the significant variables, what is the equation?
Salary =
d. Is gender a significant factor in compa-ratio?
e. Regardless of statistical significance, who gets paid more with all other things being equal?
f. How do we know?
3 After considering the compa-ratio based results in the lectures and your saalary based results, what else would you like to know
before answering our question on equal pay? Why?
4 Between the lecture results and your results, what is your answer to the question
of equal pay for equal work for males and females? Why?
5 What does regression analysis show us about analyzing complex measures?
The writer is very fast, professional and responded to the review request fast also. Thank you.
Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.
You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.
Read moreEach paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.
Read moreThanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.
Read moreYour email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.
Read moreBy sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.
Read more