The purpose of this assignment is to use predictive analyticstechniques and the graphs and charts associated with these techniquesto forecast outcomes and make business decisions.

Using specified data files, chapter example files, and templatesfrom the “Topic 1 Student Data, Template, and ExampleFiles” topic material, complete Chapter 12 Problems 28, 30, 34,46, 60, 62 (b through e), and 63 from the textbook. Use the PalisadeDecisionTools Excel software to complete these problems whererequested and applicable. Problem 60 should be completed using only Excel.

To receive full credit on the assignment, complete the following.

1. Ensure that the Palisade software output is included with yoursubmission.
2. Ensure that Excel files include the associatedcell functions and/or formulas if functions and/or formulas areused.
3. Include a written response to all narrative questionspresented in the problem by placing it in the associated Excelfile.
4. Place each problem in its own Excel file. Ensure thatyour first and last name are in your Excel file names.

APA style is not required, but solid academic writing is expected.

This assignment uses a rubric. Please review the rubric prior tobeginning the assignment to become familiar with the expectations forsuccessful completion. 28.Thefile P12_10.xlsx contains annual revenues for a convenience store. Ifyou want to forecast revenue for the next few years with the movingaverages method, what span should you use? Will any span work well?. 30.Thefile P02_28.xlsx contains total monthly U.S. retail sales data. Whileholding out the final six months of observations for validationpurposes, use the method of moving averages with one or more spans ofyour choice to forecast U.S. retail sales for the next 12 months.Comment on the performance of your model. What makes this time seriesmore challenging to forecast?34.Considerthe American Express closing price data in the fileP12_16.xlsx.a.Create a time series chart of the data. Based on what yousee, which of the exponential smoothing models do you think should beused for forecasting? Why?b.Use Holt’s exponential smoothing to forecastthese data, using no holdout period and requesting 20days of futureforecasts. Use the default smoothing constants of 0.1.c.Repeat part b,optimizing the smoothing constants. Does it make much of animprovement?d.Repeat parts a and b, this time using a holdout period of50 days.e.Write a short report to summarize your results. 46.Thefile P12_46.xlsx contains monthly time series data for total U.S.retail sales of building materials, garden equipment, and suppliesdealers.a.Is seasonality present in these data? If so, characterize theseasonality pattern.b.Use the Deseasonalize option in StatTools toforecast the deseasonalized data for each month of the next year usingthe moving average method with an appropriate span.c.Does Holt’sexponential smoothing method, with optimal smoothing constants,outperform the moving average method employed in part b? Demonstrate whyor why not.60.Thefile P12_60.xlsx lists annual revenues (in mil-lions of dollars) forNike. Create a time series graph of these data. Then superimpose a trendline with Excel’s Trendline option. Which of the possible Trendlineoptions seems to provide the best fit? Using this option, what are yourforecasts for the next two years?62.The file P12_62.xlsx contains data on a motel chain’s revenue and advertising.b.Usesimple exponential smoothing to make predictions for the motel chain’srevenues during the next four quarters.c.Use Holt’s method to makeforecasts for the motel chain’s revenues during the next fourquarters.d.Use Winters’ method to determine predictions for the motelchain’s revenues during the next four quarters.e.Which of these forecasting methods would you expect to be the most accurate for these data?63.The file P12_63.xlsx contains data on monthly U.S. permits for newhousing units (in thousands of houses).a.Using Winters’ method, findvalues of α, β, and γthat yield an RMSE as small as possible. Does thismethod track the housing crash in recent years?b.Although we have notdiscussed autocorrelation for smoothing methods, good forecasts derivedfrom smoothing methods should exhibit no substantial autocorrelation intheir forecast errors. Is this true for the forecasts in part a?c.At theend of the observed period, what is the forecast of housing salesduring the next few months?THE QUESTIONS NEED TO BE …Palisade outputs are all complete and correct, Functions and formulas are complete and accurate, Narrative answers to problems are flawless with extensive supporting details.