QuestionQuestion

A retail store has recently hired you as a consultant to advise on economic conditions. One important indicator that the retail store is concerned about is the unemployment rate. The retail store has found that an increase in the unemployment rate will cause a lack of consumer spending in their stores. Retail stores use the unemployment rate to estimate how much inventory to keep at their stores, which is important in maintaining cost effectiveness. In this consultant role you will apply calculations and research to create a predictive sales report.

You will complete this project in two parts, but will submit your work as one Word document. Copy and paste your calculations from your Excel workbook into the Word document.

The Final Project must be eight to ten pages in length, excluding title page and reference page(s) and must include at least three scholarly sources, in addition to the Job and Labor Statistics site. Be sure to format your work in accordance with APA guidelines as outlined in the Ashford Writing Center.

Part I

Calculate the mean yearly value using the average unemployment rate by month found in the “Final Project Data Set.”
Using the years as your x-axis and the annual mean as your y-axis, create a scatter plot and a linear regression line.
Answer the following questions using your scatter plot and linear regression line:
Compute the slope of the linear regression line.
Identify the Y-intercept of the linear regression line.
Identify the equation of the linear regression line in slope-intercept form.
Calculate the unemployment rate in 2016, based on the linear regression line.
Calculate the residuals of each year.
Find the latest unemployment rate in your state. You will need to go to the Bureau of Labor Statistics Website (www.bls.gov)and hover over “Subject Areas” in the top menu panel then select “State and Local Unemployment Rates” from the drop down menu under “Unemployment Rate”. Determine whether the rate in your state is within the range of the linear regression line or if it is an outlier.   
Interpret your results of the model and explain how a company could use the results to drive decision making.

PART II

Next interpret the analysis from Part I to complete the following qualitative components of the predictive sales report:
Introduce the project and its significance to the retail store.
Reference the statistical analysis that you completed in Part I and explain where the data came from, what type of analysis was done, what the findings were, and whether or not you believe the data to be accurate.
Explain your data-driven conclusions regarding the effects of the changing unemployment rate on the retail store.
Predict what could occur in the future that would change your linear regression line and therefore your prediction of sales.
Writing the Final Paper
The Final Paper:
Part I must be calculated in an Excel spreadsheet and then copied and pasted into your single Word document. You must show all work and clearly label all calculations. Excel documents will not be graded.
Part II must be double-spaced and formatted according with APA guidelines as outlined in the Ashford Writing Center. Part II should be included in the same Word document as your calculations.
Your Final Project in its entirety should be eight to ten pages in length excluding title page and reference page(s) and including all calculations.
Must include a cover page that includes:
- Title of paper
- Student’s name
- Course name and number
- Instructor’s name
- Date submitted
Must include an introductory paragraph with a succinct thesis statement.
Must address the topic of the paper with critical thought.
Must conclude with a restatement of the thesis and a conclusion paragraph.
Must use at least three scholarly resources
Must use APA style as outlined in the approved APA style guide to document all sources.
Must include, on the final page, a Reference Page that is completed according to APA style as outlined in the approved APA style guide.
You must submit your work in one Word document that includes Part I and Part II.

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Abstract
In this report we provide a forecast for the unemployment rate for the year 2016. This forecast will help you to assess the level of consumer spending for that period, and you can use it as input to adjust your business strategy – inventory management and staffing – accordingly.
The method we employ is a quite well established statistical method – linear regression. This method uses annual unemployment data over the period 1948 – 2013. These data show a clear future trend from which we predict, with reasonably high confidence, a baseline unemployment rate of around 7.1% for the year 2016.

Predictive Sales Report
Your retail store has recently hired us as to advise on economic conditions. In meetings it became clear that your store can use an assessment of the future/near term unemployment rate for business planning (inventory and staffing levels), since you have observed a direct link between the unemployment levels, and consumer confidence, and consumer spending in the store. In this report we will apply calculations and research to create a predictive sales report.
Your observation: there is a direct link between unemployment and consumer spending is well founded. It is well established that unemployment, consumer sentiment and the perception of increased job insecurity has an immediate impact on consumer and household spending. For instance, according to Benito [1], a one standard deviation increase in unemployment risk, reduces household consumption by 1.6%. Dees [2] analyzed the impact of the 2008-09 financial crisis on the real economy in the US and Europe....
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