w5 predictive sales report

| March 26, 2015

w5 predictive sales report



See attached. MUST be 8 pages, double spaced. MUST use 3 references from JSTOR or PROQUEST plus the job and statistics website and cite properly. MUST calculate in Excel but paste into Word document.

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Predictive Sales Report 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 pages in length, excluding title page and reference page(s) and must include at least three scholarly sources, from JSTOR or PROQUEST, in addition to the Job and Labor Statistics site. Be sure to format your work in accordance with APA guidelines Part I Reference the data in this http://vizedhtmlcontent.next.ecollege.com/pub/content/af6124e9-f1de-4ae1-995c-734c6f21dfe9/BUS_308_Unemployement_Data_Final_Project.xlsExcel workbook (attached) to complete the following quantitative components of the predictive sales report. You will complete the calculations below in your own Excel workbook and then copy and paste from your Excel workbook into the Word document. 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.

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