BUS 308 Week 5 Final Paper

New BUS 308 Week 5 Final Paper

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Week 5

Final Paper

The final assignment for this course is a Final Paper. The purpose of the Final Paper is for you to culminate the learning achieved in the course by creating a sales report. The Final Paper represents 25% of the overall course grade.

Writing the Final Paper

Identify an issue in your life (work place, home, social organization, etc.) where a statistical analysis could be used to help make a managerial decision. Develop a sampling plan, an appropriate set of hypotheses, and an inferential statistical procedure to test them. You do not need to collect any data on this issue, but you will discuss what a significant statistical test would mean and how you would relate this result to the real-world issue you identified. Your paper should be three to five pages in length (excluding the cover and reference pages). In addition to the text, utilize at least three sources to to support your points. No abstract is required. Use the following research plan format to structure the paper:

Step 1: Identification of the problem

Describe what is known about the situation, why it is a concern, and what we do not know.

Step 2: Research Question

What exactly do we want our study to find out? This should not be phrased as a yes/no question.

Step 3: Data collection

What data is needed to answer the question, how will we collect it, and how will we decide how much we need?

Step 4: Data Analysis

Describe how you would analyze the data. Provide at least one hypothesis test (null and alternate) and an associated statistical test.

Step 5: Results and Conclusions

Describe how you would interpret the results. For example, what would you recommend if your null hypothesis was rejected and what would you do if the null was not rejected?

A quick example: Concern if gender is impacting employee’s pay. H0: Gender is not related to pay. H1: Gender is related to pay. Approach: Multiple regression equation to see if gender impacts pay after considering the legal factors of grade, appraisal, education, etc. If regression coefficient for gender is significant, will need to create residual list to see which employees show excessive variation from predicted salaries when gender is not considered

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BUS 308 Week 5 DQ 2 Regression

BUS 308 Week 5 DQ 2 Regression

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DQ 2

Regression.

At times we can generate a regression equation to explain outcomes. For example, an employee’s salary can often be explained by their pay grade, appraisal rating, education level, etc. What variables might explain or predict an outcome in your department or life? If you generated a regression equation, how would you interpret it and the residuals from it?

Guided Response: Review several of your classmates’ posts. Respond to at least two classmates by commenting on how this information might be used to make business decisions.

BUS 308 Week 5 DQ 1 Correlation

BUS 308 Week 5 DQ 1 Correlation

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DQ 1

Correlation.

What results in your departments seem to be correlated or related to other activities? How could you verify this?

Create a null and alternate hypothesis for one of these issues. What are the managerial implications of a

correlation between these variables?

Guided Response: Review several of your classmates’ posts. Respond to at least two classmates by

explaining whether or not you think that there is a relationship between the variables discussed.

BUS 308 Week 4 DQ 2 Chi-Square Tests

BUS 308 Week 4 DQ 2 Chi-Square Tests

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DQ 2

Chi-Square Tests.

Chi-square tests are great to show if distributions differ or if two variables interact in producing outcomes. What are some examples of variables that you might want to check using the chi-square tests? What would these results tell you?

Guided Response: Review several of your classmates’ posts. Respond to at least two classmates by commenting on how this information might be used to make business decisions.

BUS 308 Week 4 DQ 1 Confidence Intervals

BUS 308 Week 4 DQ 1 Confidence Intervals

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DQ 1

Confidence Intervals.

Earlier we discussed issues with looking at only a single measure to assess job-related results. Looking back at the data examples you have provided in the previous discussion questions on this issue, how might adding confidence intervals help managers understand results better?

Guided Response: Review several of your classmates’ posts. Respond to at least two classmates by commenting on whether or not you think changing the confidence intervals will result in a different outcome. Explain if you agree or disagree with the role of a confidence interval in the interpretation of the answer.

BUS 308 Week 4 Assignment Problem Set Week Four

BUS 308 Week 4 Assignment Problem Set Week Four

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Problem Set Week Four

Let’s look at some other factors that might influence pay. Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the Employee Salary Data set (in Appendix section).

Is the probability of having a graduate degree independent of the grade the employee is in?

Construct a 95% confidence interval on the mean service for each gender. Do they intersect?

Are males and females distributed across grades in a similar pattern?

Do 95% confidence intervals on the mean length of service for each gender intersect?

How do you interpret these results in light of our equity question?

BUS 308 Week 3 DQ 2 Effect Size

BUS 308 Week 3 DQ 2 Effect Size

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DQ 2

Effect Size

Several statistical tests have a way to measure effect size. What is this, and when might you want to use it in looking at results from these tests on job related data?

Guided Response: Review several of your classmates’ posts. Respond to at least two of your classmates and…