A well-known multinational FMCG produces more than fifty products and sells them in the market. Out of fifty products one is mineral water for drinking purpose and supplies different size pack bottles in the market. Product manager observed that, during hot days the sale of water is more as compared to the normal days. He started the collection of data of weekly sale of water and the average weekly temperature. Product manager was interested in developing a relationship between sales and temperature; therefore, he discussed and shared the following data with you

A well-known multinational FMCG produces more than fifty products and sells them in the market. Out of fifty products one is mineral water for drinking purpose and supplies different size pack bottles in the market. Product manager observed that, during hot days the sale of water is more as compared to the normal days. He started the collection of data of weekly sale of water and the average weekly temperature. Product manager was interested in developing a relationship between sales and temperature; therefore, he discussed and shared the following data with you

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.4: Multiple Regression Models

Problem 17P: The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He...

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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?
Under what conditions might a firm use multiple forecasting methods?
The Flamingo Grill is an upscale restaurant located in St. Petersburg, Florida. To help plan an advertising campaign for the coming season, Flamingo’s management team hired the advertising firm of Haskell & Johnson (HJ). The management team requested HJ’s recommendation concerning how the advertising budget should be distributed across television, radio, and newspaper advertisements. The budget has been set at $279,000. In a meeting with Flamingo’s management team, HJ consultants provided the following information about the industry exposure effectiveness rating per ad, their estimate of the number of potential new customers reached per ad, and the cost for each ad. Advertising Media Exposure Rating per Ad New Customes per Ad Cost per Ad Television 90 4000 $10,000 Radio 25 2000 $3,000 Newspaper 10 1000 $1,000 The exposure rating is viewed as a measure of the value of the ad to both existing customers and potential new customers. It is a function of such things as image,…
The Flamingo Grill is an upscale restaurant located in St. Petersburg, Florida. To help plan an advertising campaign for the coming season, Flamingo’s management team hired the advertising firm of Haskell & Johnson (HJ). The management team requested HJ’s recommendation concerning how the advertising budget should be distributed across television, radio, and online advertisements. The budget has been set at $279,000. In a meeting with Flamingo’s management team, HJ consultants provided the following information about the industry exposure effectiveness rating per ad, their estimate of the number of potential new customers reached per ad, and the cost for each ad: Advertising Exposure Rating New Customers Cost per Ad Media per Ad per Ad Television 90 4000 $10,000 Radio 25 2000 $3,000 Online 10 1000 $1,000 The exposure rating is viewed as a measure of the value of the ad to both existing customers and potential new customers. It is a function of such things as…
1. The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Part 2 Week Of Pints Used August 31 350 September 7 372 September 14 412 September 21 381 September 28 366 October 5 378 Part 3 a) The forecasted demand for the week of October 12 using a 3-week moving average LOADING... = _____________pints (round your response to two decimal places).
Develop the first three steps of the management–research question hierarchy namely i) management dilemma ii) management question iii) research question(s), for the following scenario A- The owner of city resturant in fairfax.
GHM Company is a well-known automotive company in the United States. GHM has tracked the monthly sales of their main product, Ranger, over the past three years. GHM believes that there is an effect of seasons in their sales. Following are the results of CMA analysis of the monthly sales: a. Complete the table and calculate the Seasonal Index for all quarters. b. What is the interpretation of the seasonal index value?
A. Find the tracking signal for each month. B. Does the model provide acceptable answers!
Exercise # 2 –Calculating MADt, Revised MADt,Error,and the Revised Error :Has the Forecast Improved ? How much has it improved in % terms ? Franklin Henry forecasts demand for an auditing and accounting services group, for an estate planning group ,and a business consulting group.His group forecasts for the preceding six-month(M) period, which were made six months prior to that time, are each based on a level, patternless projection.The following data table shows these forecasts(F) and the actual demand (AD) for each group : Estate Planning Auditing and Accounting Business Consulting (Client –days) (Client –days) (Client –days) M AD F M AD F M AD F 1 120 130 1 260 230 1 120 120 2 80 130…
Chart and Regression analysis : What does the intercept predict? X: C16 (number of cars on the sales lot) versus Y: C17 (cars sold per day) Equation: y=2.9x + 14.5 Slope:2.9 Intercept:14.5 Does the intercept mean the intercept is 14.5 means that the cars sold per day( Y) predicted number of cars on sale lot(X) to be 14.5, but this intercept has no meaning. So, I will not use to predict cars sold per day?
A small local grocery has seen a decline in sales in the past few months. The owner has made no changes to the store in the last year. In the beginning, the owner thought the sales drop might be seasonal. However, looking at the past few years of sales data, the owner noticed that there had not been any decrease in sales during the same time in the previous years. Design a study to identify what might be the probable ultimate cause/s of the decline in sales for a grocery. For looking at the different causes, consider the box and arrow diagram given. Note the following things about the box and arrow diagram: If the arrow’s head is towards a box, that means the variable in the box (where the arrow’s head is) affects the variable in the box from where the arrow originated. E.g “Revenue/Sales” is affected by the “Number of shoppers/customers”. The boxes in grey are the variables you as a firm/owner can directly expect to affect which can further affect other variables in the model. E.g.…
A small local grocery has seen a decline in sales in the past few months. The owner has made no changes to the store in the last year. In the beginning, the owner thought the sales drop might be seasonal. However, looking at the past few years of sales data, the owner noticed that there had not been any decrease in sales during the same time in the previous years. Design a study to identify what might be the probable ultimate cause/s of the decline in sales for a grocery. For looking at the different causes, consider the box and arrow diagram given. Note the following things about the box and arrow diagram: If the arrow’s head is towards a box, that means the variable in the box (where the arrow’s head is) affects the variable in the box from where the arrow originated. E.g “Revenue/Sales” is affected by the “Number of shoppers/customers”. The boxes in grey are the variables you as a firm/owner can directly expect to affect which can further affect other variables in the model. E.g.…