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- The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
- Can someone simply explain linear regression? Can linear regression be automatically calculated in SPSS?The classified department of a monthly magazine has used a combination of quantitative and qualitative methods to forecast sales of advertising space. Results over a 20-month period are as follows:Month Error1 −8 2 −2 3 4 4 7 5 9 6 5 7 0 8 −3 9 −9 10 −4 11 1 12 6 13 8 14 4 15 1 16 −2 17 −4 18 −8 19 −5 20 −1 a. Compute a tracking signal for months 11 through 20. Compute an initial value of MAD for month 11, and then update it for each month using exponential smoothing with α = .1. What can you conclude? Assume limits of ± 4.b. Using the first half of the data, construct a control chart with 2s limits. What can you conclude?c. Plot the last 10 errors on the control chart. Are the errors random? What is the implication of this?A Problem Set 3-edited Mailings Review View Tell me AaBbCcDdEe AaBbCcDdEe AaBbCcDdEe AaBbCcDdEe Normal Body Text List Paragraph No Spacing 5. Table 1 shows the daily stock price of Apple Inc. (AAPL) in the past few trading days. Table 1. Daily stock prices of Apple Inc. 1- 4- 5- 6- 7- 8- 11- 12- 13- 14- 15- 18- Date Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Nov Stock 255.1 256.7 256.4 256.5 259.4 260.1 262.2 262 264.5 262.6 265.8 265.7 Price Since the stock market closes on weekends, Table 1 only shows stock prices during weekdays. Please answer the following questions based on the given information. (a) Apply the moving average (MA) model with a three-day lag (q = 3) and a five-day lag (q =5) to forecast Apple Inc.'s stock price in the following three trading days (i.e., its stock price on November 19, 20 and 21). (Hint: calculate the stock price on November 19 first, and then use the estimated stock price of November 19 to forecast the stock price on November 20.) (ROUND TO ONE…
- What is differ from SMA (Simple moving average), WMA (Weighted moving average), SLR (Single linear regression), and ESM ( Exponential smoothing model).Why would we graph scatterplots and regression lines?Check if all right. Which one is wrong about time horizons. Medium/long range forecasts deal with more comprehensive issues and support management decisions regarding planning and products, plants and processes. Short-term forecasting usually employs different methodologies than longer-term forecasting. Short-term forecasts tend to be more accurate than longer-term forecasts Economic forecasts: Address business cycle - inflation rate, money supply, housing starts, etc What is the objective of process design? The objective is to create umbrella term for manufacturing processes that use irregular production schedules to create several different products using one production line. The objective is to create high degree of product flexibility The objective is to create facilities are organized around specific activities or processes The objective is to create a process to produce offerings that meet customer requirements within cost and other managerial constraints What is benefit of…
- Graph the provided data as the correct graph typeDiscuss how the coefficient of determination and the coefficient of correlation are related and how they are used in regression analysis. Be sure to provide examples to illustrate your understanding of these concepts.The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week of Pints Used August 31 360 September 7 370 September 14 412 September 21 383 September 28 371 October 5 371 a) The forecasted demand for the week of October 12 using a 3-week moving average= {__] Pints (round your response to two decimal places).