The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months:MonthJanNumber of Accidents 25Feb48Mar64Apr100Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places):y = -1 + 24.10 xUsing least-squares regression, the forecast for the number of accidents that will occur in the month of Mayresponse as a whole number).=accidents (enter your

The least square regression model considers Y=a+bx. Here, "a" indicates intercept and "b" indicates…

Answered: The following gives the number of…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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Tom Simpson, Director of the Chamber of Commerce for Exeter township is investigating the past ten years of tourist visits to the area. The following data has been gathered on number of tourists who signed into the local information center. Year Number of tourists 1 700 2 248 3 633 4 458 5 1410 6 1588 7 1629 8 1301 9 1455 10 1989 What is the forecasts for Year 11 using the simple moving method? (show in calculations in excel file)
Demand for oil changes at Garcia's Garage has been as follows: Month January February March April May June July August Number of Oil Changes 38 55 56 60 58 01 70 52 a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For January, let X=1; for February, let X 2; and so on. The forecasting model is given by the equation Y=X (Enter your responses rounded to two decimal places)
Please forecast the mileage (in 100) for 2013 using a 4 period moving average method. Please keep 1 decimal place.
A security company had to deploy guards for emergencies multiple times in the last four evenings. The numbers of emergencies for Monday, Tuesday, Wednesday, and Thursday were 7, 4, 8, and 11, respectively. What would be the security company's forecast for the number of emergencies on Friday using an exponential smoothing forecasting approach? (Use \alpha= 0.2 and a forecast for Monday of 10 emergencies)
Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the previous month. Gershon has collected the data shown in the following table: Maroon 5 TV Appearances 3 3 8 5 8 6 Demand for Guitars 2 5 6 4 11 6 This exercise contains only parts b, c, and d. b) Using the least-squares regression method, the equation for forecasting is (round your responses to four decimal places): Y = + c) The estimate for guitar sales if Maroon 5 performed on TV 11times = sales (round your response to two decimal places). d) The correlation coefficient (r)for this model = (round your response to four decimal places). The coefficient of determination (r2) for this model = (round your response to…
Using least-squares regression, the forecast for the number of accidents that will occur in the month of May = ? accidents (enter your response as a whole number).
Hi, I need help with solving for the following values (boxed). Thank you.
The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Jan Feb Mar AprMonth 1 2 3 4Number of Accidents 25 40 60 105 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): y = ? + ?x
Develop two exponential smoothing forecasts for periods 2 through 11. For the first forecast, use a=0.1. For the second, use a=0.7. Assume that your forecast for period 1 was 205. Click the icon to view the time series data. Find the exponential smoothing forecast for each period when a=0:1 (enter your responses rounded to one decimal place). Period Forecast (0.1) 205 1 2 More Info Period 1 2 3 4 5 6 7 8 9 10 Print Demand 228 249 229 238 231 154 166 157 Demand 228 249 164 161 Done
The accompanying dataset provides data on the monthly usage of natural gas (in millions of cubic feet) for a certain region over two years. Implement the Holt-Winters multiplicative seasonality model with no trend to find the forecast for periods 13-26, where x = 0.5 and y = 0.8. Then find the MAD for periods 13-24. Click the icon to view the monthly use of natural gas data. Use the Holt-Winters multiplicative seasonality model with no trend to find the forecast for periods 13-18, periods 19-24, and then for periods 25 and 26. (Type integers or decimals rounded to two decimal places as needed.) Forecast Period 13 14 15 16 17 18 Natural Gas Usage Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Period Gas Usage 1 2 8699 A WI 3 4 5 7 9 10 11 12 13 14 1516718192021 22 23 24 241 221 155 137 54 34 29 27 30 40 90 201 229 238 242 136 34 34 28 26 27 40 86 187
Amazon finds that sales in July are much greater relative to other months because of the Amazon Prime days in that month. Assuming that an exponential smoothing model is used for forecasting sales, what should the company best do to make the forecast for the next month (Aug) more reflective of reality? Please pick from the provided options. F t+1 = αDt + (1-α) Ft increase value of alpha decrease value of alpha stay with the same alpha decrease the expected forecast for the current month (Ft) On hearing our forecast, our clients probe - how sure are we about the forecast? Which measure of errror (among those stated below) should we best use to respond? a. Root MSE (RMSE) b. Mean absolute percentage error (MAPE) c. Mean forecast error (Avg. error) d. Cumulative forecast error (CFE)
Given the following historical data, what is the simple three-period moving average forecast for period 6? Period 1 2 3 4 5 67.67 68.2 67.3 68.4 Value 73 66 64 73 66

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