Tandoori Lovers, periodically offers take away chicken combo dinners at special prices. Based on historical observations and calculations in the following table, determine the regression equation, correlation coefficient and coefficient of determination. Forecast the sales of Chicken Palace's chicken combo dinner set if it is priced at RM4.50 each. Observation Price (RM) Combo dinners sold 1 2.70 760 2 3.50 510 3 2.00 980 4.20 250 4 3.10 320 5 4.05 480

Tandoori Lovers, periodically offers take away chicken combo dinners at special prices. Based on historical observations and calculations in the following table, determine the regression equation, correlation coefficient and coefficient of determination. Forecast the sales of Chicken Palace's chicken combo dinner set if it is priced at RM4.50 each. Observation Price (RM) Combo dinners sold 1 2.70 760 2 3.50 510 3 2.00 980 4.20 250 4 3.10 320 5 4.05 480

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

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Under what conditions might a firm use multiple forecasting methods?
The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
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?
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_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
Year Season Sales 2018 Winter 40 2018 Spring 29 2018 Summer 31 2018 Fall 40 2019 Winter 102 2019 Spring 87 2019 Summer 96 2019 Fall 132 2020 Winter 105 2020 Spring 93 2020 Summer 105 2020 Fall 117 2021 Winter 141 2021 Spring 39 2021 Summer 114 2021 Fall 123 What is the slope of the trend equation obtained by linear regression? Round to two decimal digits. What is the intercept of the trend equation obtained by linear regression? Round to two decimal digits. What is the seasonal index for Spring? Round to two decimal digits. The quarter number for Winter of 2018 is 1. What is the quarter number for Spring of 2025? What is the trend based forecast for Spring of 2025. Round to a whole number. What is the seasonally adjusted trend based forecast for Spring of 2025? Please do not use excel to find the slope and intercept, thank you so much!
The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES 1 215 2 240 3 205 4 190 5 160 6 195 7 150 8 140 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to 1 decimal place.
The number of patients coming to the Healthy Start Maternity clinic has been increasing steadilyover the past eight months. You are provided with some historical data as follows: Month Clinic attendance (in thousands)1 3.42 3.93 4.54 5.05 5.86 5.97 6.58 6.7 a. Identify and give a brief explanation of the:i. Dependent variableii. Independent variable b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:i. Derive the values for the intercept and slope. ii. Derive the linear regression equation. iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.
The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES QUARTER SALES 1. 211 5 155 235 6 198 3 206 7 154 4 190 8 142 Use regression and seasonal indexes to forecast quarterly sales for the next year. (Do n ot round intermediate calculations. Round your answers to the nearest whole number.) Answer is complete but not entirely correct. Quarter Forecast 142 8 157 8 121 8 10 11 12 103
The number of patients coming to the Healthy Start Maternity clinic has been increasing steadily over the past eight months. You are provided with some historical data as follows:Month Clinic attendance (in thousands) 1 3.42 3.93 4.54 5.05 5.86 5.97 6.58 6.7a. Identify and give a brief explanation of the:-i. Dependent variableii. Independent variable b. Use simple linear regression to forecast annual demand for months 9 and 10 by using the tabular method to:-i. Derive the values for the intercept and slope. ii. Derive the linear regression equation.iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.
A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales duringthe last 15 days wereDay: 1 2 3 4 5 6 7 8 9Number sold: 36 38 42 44 48 49 50 49 52Day: 10 11 12 13 14 15Number sold: 48 52 55 54 56 57a. Using linear trend equation method, predict future sales from the given data.b. If you learn that on some days the store ran out of the specific pain reliever, would that knowledge cause you any concern? Explain.
Answer in Excel: Consider the data below for the sales of widgets: 1. Using seasonal percentages or seasonal indexes, forecast the sales for each season in year 4, if the annual widgets sales is predicted to be 1500. 2. Develop a regression equation that captures both the trend and seasonality in this data. Use this equation to forecast the sales for each season in year 4. Season Year 1 Year 2 Year 3 Fall 505 240 210 Winter 555 460 365 Spring 400 310 204 Summer 560 450 394