Mathematics
Statistics Questions Need Excel Spreadsheet Filled Out

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I need support with this Mathematics question so I can learn better.

I need the questions is Mat540 wk 4 answered in the answer sheet for week 4.


mat540 hw wk4(2).docx 

HW4_answer_sheet 2014-0701(3).xlsx 


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MAT540 Homework Week 4 Page 1 of 4 MAT540 Week 4 Homework Chapter 15 2. The manager of the Carpet City outlet needs to make an accurate forecast of the demand for Soft Shag carpet (its biggest seller). If the manager does not order enough carpet from the carpet mill, customers will buy their carpet from one of Carpet City’s many competitors. The manager has collected the following demand data for the past 8 months: Month 1 2 3 4 5 6 7 8 Demand for Soft Shag Carpet (1,000 yd.) 8 12 7 9 15 11 10 12 a. Compute a 3-month moving average forecast for months 4 through 9. b. Compute a weighted 3-month moving average forecast for months 4 through 9. Assign weights of 0.55, 0.33, and 0.12 to the months in sequence, starting with the most recent month. c. Compare the two forecasts by using MAD. Which forecast appears to be more accurate? 6. The manager of the Petroco Service Station wants to forecast the demand for unleaded gasoline next month so that the proper number of gallons can be ordered from the distributor. The owner has accumulated the following data on demand for unleaded gasoline from sales during the past 10 months: Month October November December January February March April May June July Gasoline Demanded (gal.) 800 725 630 500 645 690 730 810 1,200 980 MAT540 Homework Week 4 Page 2 of 4 a. Compute an exponentially smoothed forecast, using an α value of 0.30. b. Compute the MAPD. 9. Emily Andrews has invested in a science and technology mutual fund. Now she is considering liquidating and investing in another fund. She would like to forecast the price of the science and technology fund for the next month before making a decision. She has collected the following data on the average price of the fund during the past 20 months: Month 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Fund Price $63 1/4 60 1/8 61 3/4 64 1/4 59 3/8 57 7/8 62 1/4 65 1/8 68 1/4 65 1/2 68 1/8 63 1/4 64 3/8 68 5/8 70 1/8 72 3/4 74 1/8 71 3/4 75 1/2 76 3/4 a. Using a 3-month average, forecast the fund price for month 21. b. Using a 3-month weighted average with the most recent month weighted 0.60, the next most recent month weighted 0.30, and the third month weighted 0.10, forecast the fund price for month 21. c. Compute an exponentially smoothed forecast, using α=0 .40, and forecast the fund price for month 21. d. Compare the forecasts in (a), (b), and (c), using MAD, and indicate the most accurate. 26. Carpet City wants to develop a means to forecast its carpet sales. The store manager believes that the store’s sales are directly related to the number of new housing starts in town. The manager has gathered data from county records on monthly house construction permits and from store records MAT540 Homework Week 4 Page 3 of 4 on monthly sales. These data are as follows: Monthly Carpet Sales (1,000 yd.) 5 10 4 3 8 2 12 11 9 14 Monthly Construction Permits 21 35 10 12 16 9 41 15 18 26 a. Develop a linear regression model for these data and forecast carpet sales if 30 construction permits for new homes are filed. b. Determine the strength of the causal relationship between monthly sales and new home construction by using correlation. 27. The manager of Gilley’s Ice Cream Parlor needs an accurate forecast of the demand for ice cream. The store orders ice cream from a distributor a week ahead; if the store orders too little, it loses business, and if it orders too much, the extra must be thrown away. The manager believes that a major determinant of ice cream sales is temperature (i.e., the hotter the weather, the more ice cream people buy). Using an almanac, the manager has determined the average daytime temperature for 10 weeks, selected at random, and from store records he has determined the ice cream consumption for the same 10 weeks. These data are summarized as follows: Week 1 2 3 4 5 6 7 8 9 10 Average Temperature (degrees) 73 65 81 90 75 77 82 93 86 79 Ice Cream Sold (gal.) 110 95 135 160 97 105 120 175 140 121 a. Develop a linear regression model for these data and forecast the ice cream consumption if the average weekly daytime temperature is expected to be 85 degrees. MAT540 Homework Week 4 Page 4 of 4 b. Determine the strength of the linear relationship between temperature and ice cream consumption by using correlation. 28. Compute the coefficient of determination for the data in Problem 27 and explain its meaning. Carpet City Month 1 2 3 4 5 6 7 8 9 Demand for Soft Shag Carpet (1,000 yd.) 8 12 7 9 15 11 10 12 3 mos moving Weighted 3 mos moving average forecast average forecast Please apply weights stated in the problem Compute MAD on 3 mos moving average Compute MAD on weighted 3 mos moving average Which is a better forecast method? Petroco Service Station alpha = 0,3 Month October November December January February March April May June July Gas Demand 800 725 630 500 645 690 730 810 1200 980 7710 Exp Forecast Error 777,5 0,00 MAPD 0,00% SUM Science and Technology Mutual Fund Month Fund Price 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 63 1/4 60 1/8 61 3/4 64 1/4 59 3/8 57 7/8 62 1/4 65 1/8 68 1/4 65 1/2 68 1/8 63 1/4 64 3/8 68 5/8 70 1/8 72 3/4 74 1/8 71 3/4 75 1/2 76 3/4 alpha = 3 mos moving average forecast 0,4 Compute MAD on 3 mos moving average Compute MAD on weighted 3 mos moving average Compute MAD on exponentially smoothed forecast Which is a better forecast method? Weighted 3 mos moving average forecast Please apply weights stated in the problem Exp Forecast Carpet City Regression Monthly Carpet Sales Monthly Construction (1,000 yd.) Permits 5 10 4 3 8 2 12 11 9 14 21 35 10 12 16 9 41 15 18 26 Place regression output here If 30 construction permits issued What is expected carpet sales (1000 yds)? Correlation Coefficient Gilley's Ice Cream Parlor Week 1 2 3 4 5 6 7 8 9 10 x y Ave. Temp (degrees) 73 65 81 90 75 77 82 93 86 79 Ice cream Sold (gal.) 110 95 135 160 97 105 120 175 140 121 Place regression output here If average 85 deg weekly daytime temperature What is expected ice cream sold? Correlation Coefficient Coefficient of Determination ...
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