Calf Prices 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 A B Week 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Price $176 $172 $174 $177 $173 $171 $172 $173 $174 $173 $171 $172 $174 $177 $180 $178 $176 $179 $175 $176 $174 $175 Page 1 3. Each month, Joe's Auto Parts uses exponential smoothing (with a = 0.25) to predict the number of cans of brake fluid that will be sold during the next month. In June, Joe forecast that he would sell 37 cans of brake fluid during July. Joe actually sold 43 cans in July. a. What is Joe's forecast for brake fluid sales in August and September? b. Suppose that Joe sells 32 cans of brake fluid in August. What is the revised fore- cast for September? Questions 4 through 10 refer to the data in the file that accompanies this book named SmallBusiness.xlsx representing annual sales (in $1000s) for a small business. 4. Prepare a line graph of these data. Do the data appear to be stationary or nonstationary? 5. Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the orig- inal data. b. Do the moving averages tend to overestimate or underestimate the actual data? Why? C. Compute forecasts for the next two years using the two-period and four-period moving average techniques. 6. Use Solver to determine the weights for a three-period weighted moving average that minimizes the MSE for the data set. What are the optimal values for the weights? b. Prepare a line graph comparing the weighted moving average predictions against the original data. What are the forecasts for the next two years using this technique? 7. Create a double moving average model (with k = 4) for the data set. a. Prepare a line graph comparing the double moving average predictions against the original data. b. What are the forecasts for the next two years using this technique? 8. Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to determine the optimal value of a. a. c. Questions 30 through 34 refer to the data in the file that accompanies this book named CalfPrices.xlsx representing the selling price of three-month-old calves at a livestock auction during the past 22 weeks. 30. Prepare a line graph of these data. Do the data appear to be stationary or nonstationary? 31. Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the orig- inal data. b. Compute the MSE for each of the two moving averages. Which appears to pro- vide the best fit for this data set? C. Compute forecasts for the next two weeks using the two-period and four-period moving average techniques. 32. Use Solver to determine the weights for a four-period weighted moving average on the data set that minimizes the MSE. a. What are the optimal values for the weights? b. Prepare a line graph comparing the weighted moving average predictions against the original data. What are the forecasts for weeks 23 and 24 using this technique? 33. Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to estimate the optimal value of a. a. What is the optimal value of a? b. Prepare a line graph comparing the exponential smoothing predictions against the original data. What are the forecasts for weeks 23 and 24 using this technique? 34. Use Holt's method to create a model that minimizes the MSE for the data set. Use Solver to estimate the optimal values of a and B. a. What are the optimal values of a and B? b. Are these values surprising? Why or why not? C. C. Forecasting Techniques 1 Unsatisfactory 0.00% 2 Less than Satisfactory 74.00% 3 Satisfactory 79.00% 4 Good 87.00% 5 Excellent 100.00% 100.0 % Content 20.0 % Excel Outputs Excel outputs are not included. Excel outputs are incomplete or incorrect. Excel outputs are included with some errors in accuracy. Excel outputs are included and mostly accurate. Excel outputs are all complete and correct. 20.0% Functions and Formulas Functions and formulas are not included. Functions and formulas are incomplete or incorrect. Functions and formulas are included but lack accuracy. Functions and formulas are included and mostly accurate, Functions and formulas are complete and accurate, 20.0 % Narrative Answers to Problems Narrative answers to problems are not included. Narrative answers to problems are incomplete or incorrect. Narrative answers to problems are included but lack accuracy and detail. Narrative answers to problems are complete and include relevant details. Narrative answers to problems are flawless with extensive supporting details. 30.0 % Executive Summary Executive summary, including discussion of data analysis findings, description of the data Executive summary, including discussion of data analysis findings, description of the data Executive summary, including discussion of data analysis findings, description of the data Executive summary, including discussion of data analysis findings, description of the data Executive summary including discussion of data analysis findings, description of the data 30.0 % Executive Summary Executive summary, including discussion of data analysis findings, description of the data patterns, a data- based forecast, and justification, is not included. Executive summary, including discussion of data analysis findings, description of the data patterns, a data- based forecast, and justification, is incomplete or incorrect. Executive summary, including discussion of data analysis findings, description of the data patterns, a data- based forecast, and justification, is included but lacks relevant details. Executive summary, including discussion of data analysis findings, description of the data patterns, a data- based forecast, and justification, is complete and includes relevant details. Executive summary including discussion of data analysis findings, description of the data patterns, a data- based forecast, and justification, is expertly crafted and includes extensive relevant details. 10.0 % Mechanics of Writing (includes spelling, punctuation, grammar, language use) Surface errors are pervasive enough that they impede communication of meaning. Inappropriate word choice or sentence construction is used. Writer is clearly in command of standard, written, academic English. Frequent and repetitive mechanical errors distract the reader. Inconsistencies in language choice (register) or word choice are present. Sentence structure is correct but not varied. Some mechanical errors or typos are present, but they are not overly distracting to the reader. Correct and varied sentence structure and audience- appropriate language are employed. Prose is largely free of mechanical errors, although a few may be present. The writer uses a variety of effective sentence structures and figures of speech. Total Weightage 100 %
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