What would be the simple linear regression (trend projection) forecast for week 4 and for week 53 for Small Town Restaurant (see file) if the regression equation for our data is: y = 3061.7 + 0.2364x ? Provide two decimal places and use normal rounding. ¶¶Situation: The "Small Town Restaurant" uses a forecast of weekly sales revenue to plan theirinventory ordering and staffing for the upcoming week. They have been using a regressionforecast for the past year and wonder if it is the most accurate method. You have been brought into determine if another forecasting technique would be more accurate. Data for their weeklysales for the past year is below:¶Week Revenue. X Week12 $3,0163 $3,062.¤ ¤4$ 3,074. X5$3,002.6----3,054-¤¤7 $3,002.¤ ¤89$3,078¤ ¤10 $3,010- X11 $3,148.12$3,146$3,198.13X¶$3,157.**$Forecasting S$ 2,984-¤¤A- Small Town RestaurantRevenue.14 $3,157 ¤$3,016¤1516 $3,019¤17 $3,045¤1819$3,046 ¤$3,157 ¤$3,016 ¤$3,078 ¤22 $2,9842021¤23 $3,002 ¤24 $3,054 ¤25 $3,002 ¤26 $2,941 XAWeekRevenue.27 $2,899 ¤28 $2,942¤29 $3,062 X¤30 $3,07431 $3,013 ¤¤32 $3,06733 $3,148 ¤34 $3,146¤35 $3,198 ¤36 $3,082 ¤37 $3,146 ¤38 $3,150 ¤39 $3,221 ¤XBWeek Revenue. ¤40 $3,298.41 $3,201.42 $3,156.43 $3,017. X44 $3,156.45 $3,097.46 $ 2,978. X47 $3,12048 $3,156.49 $3,048.50 $2,948.51 $ 2,840.52 $2,921.X$ 159,532 Annual totalYou will use this data in the next few steps to complete various time series forecasts andcompare them to determine the most accurate method.¤¤¤¤¤¤¤¤¤¤¤¤¤¤¤X{X{X{X{

The data on weekly sales revenue is given.The regression equation for our data is: y = 3061.7 +…

1 Situation: The "Small Town Restaurant" uses a forecast of weekly sales revenue to plan their inventory ordering and staffing for the upcoming week. They have been using a regression forecast for the past year and wonder if it is the most accurate method. You have been brought in to determine if another forecasting technique would be more accurate. Data for their weekly sales for the past year is below: 1 Forecasting-Small Town Restaurant Week Revenue B Week 1x $3,157. 14 2 $3,016 15 3 $3,062¤ ¤ 16 4 $3,074¤ ¤ 17 5 $3,002-¤¤ 18 $3,046 6 $3,054-¤¤ 19 $3,157 ¤ 7 $3,002-¤¤ 20 $3,016 8 $ 2,984¤ ¤ 21 $3,078 ¤ 9 $3,078¤ ¤ 22 $2,984 ¤ 10 $3,010- 23 $3,002 11 $3,148 24 $3,054 ¤ 12 25 $3,002 ¤ $3,146 $3,198 13 26 $2,941 X ¤ ¤ Revenue $3,157 ¤ $3,016 ¤ $3,019 ¤ $3,045 ¤ Revenue. 27 $2,899 ¤ ¤ 28 $2,942 29 $3,062 ¤ 30 $3,074 ¤ 31 $3,013 ¤ 32 $3,067 ¤ 33 $3,148 34 $3,146 ¤ 35 $3,198 ¤ 36 $3,082 ¤ 37 $3,146 ¤ 38 $3,150 ¤ 39 $3,221 Week Week Revenue B 40 $3,298 41 $3,201. 42 $3,156 43 $3,017. 44 $3,156. 45 $3,097. 46 $2,978 ¤ ¤ 47 $3,120 48 $3,156 49 $3,048 50 $2,948 51 $ 2,840 52 $2,921. $ 159,532 Annual total You will use this data in the next few steps to complete various time series forecasts and compare them to determine the most accurate method.

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...