Refer to the following null hypothesis formulated by a restaurant manager who wanted to investigate the factors that encourage the customers to return to their restaurant in future. Identify which data analysis method is the most appropriate for the null hypothesis below. * "There is no relationship between Return in Future and Service Quality, Food Quality and Food Presentation". O ttest one-way ANOVA O correlation O multiple regression

Refer to the following null hypothesis formulated by a restaurant manager who wanted to investigate the factors that encourage the customers to return to their restaurant in future. Identify which data analysis method is the most appropriate for the null hypothesis below. * "There is no relationship between Return in Future and Service Quality, Food Quality and Food Presentation". O ttest one-way ANOVA O correlation O multiple regression

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 40P: The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels....

See similar textbooks

Similar questions

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 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?
Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.
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.
Regression and Utility Rates; Sustainability For several years, many utilities haveemployed regression analysis to forecast monthly utility usage by residential customers usingweather forecasts, the number of holidays, the number of days in the month, and other factors.For example, the Connecticut Department of Public Utility Control (CDPUC) has determinedthat regression, properly used, can accurately predict natural gas usage. Most public gas utilities serving Connecticut have reported levels of accuracy from 4% to 10% using regression.One company, Dominion Natural Gas Company of Ohio, uses this approach not to forecast, butto explain to customers why their natural gas bills have gone up or down compared to the priormonth and to the same month of the prior year. The bill shows total MCF (thousand cubic feetof natural gas) used by the customer for that month and why the total MCF usage has changed,based on three factors:1. Change in temperature. Each degree increase in temperature…
a) Using the trend-projection (regression) method, develop a forecastfor the sales of Volkswagen Beetles in Nevada through year 6.b) What is the MAD?~c) What is the MSE?
Global Bikes Inc. (a bicylce manufacturing firm) collected the following data during a study of consumer buying patterns. Observation 1 2 3 4 5 6 7 y= X y 15 70 28 79 38 89 35 86 49 97 42 97 30 82 y = Observation 0.721 + 1890123 a. Create a linear regression line (equation) for the data.(Round your Intermediate calculations and final answers to 3 decimal places.) X 14 16 14 24 21 29 63.229 X y 82 70 68 84 83 91 b. Use the equation determined in part b to predict the expected value of y for x = 49. (Round your Intermediate calculations and final answers to 3 decimal places.)
Happy Lodge Ski Resorts tries to forecast monthlyattendance. Th e management has noticed a direct relationshipbetween the average monthly temperature and attendance.(a) Given fi ve months of average monthly temperatures andcorresponding monthly attendance, compute a linearregression equation of the relationship between the two.If next month’s average temperature is forecast to be 45degrees, use your linear regression equation to develop aforecast. (b) Compute a correlation coefficient for the data anddetermine the strength of the linear relationship betweenaverage temperature and attendance. How good apredictor is temperature for attendance?
Regression analysis. The owner of a small hardware store has noted a sales pattern for window locks that seems to parallel the number of break-ins reported each week in the newspaper. The data are: Sales: 46 18 20 22 27 34 14 37 30Break-ins: 9 3 3 5 4 7 2 6 4a. Plot the data to determine which type of equation, linear or nonlinear, is appropriate.b. Obtain a regression equation for the data.c. Estimate average sales when the number of break-ins is five.
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.
1- A pharmacist has been monitoring sales of certain over-the-counter pain reliever. Daily sales during the last 15 days were as follows: Day 1 2 3 4 7 8 9 Number sold 36 38 42 44 48 49 50 49 52 Day 10 11 12 13 14 15 Number sold 48 52 55 54 56 57 a: By using linear regression method predict the future sales for the next 5 days (please do all calculations in excel and send the excel file with answers included as your response) b: calculate the MSE for the prediction of these 15 days. (again by using Excel) 1- Explain how QFD can be employed for designing a new restaurant in your region in Iraq? (at least 100 words) 2- A producer of inkjet printers is planning to add a new production line of printers, and you have been asked to balance the process, given the following task times and precedence relationships. Assume the cycle time is to be minimum possible (based on the bottleneck). Immediate Length (minutes) Task (Predecessor) a 0.2 b 0.4 a 0.3 d 1.3 b, c e 0.1 f 0.8 e g 0.3 d, f 1.2 g a…
The following data relate the sales figures of the barin Mark Kaltenbach’s small bed-and-breakfast inn in Portand, tothe number of guests registered that week:WEEK GUESTS BAR SALES1 16 $3302 12 2703 18 3804 14 300 a) Perform a linear regression that relates bar sales to guests (notto time).b) If the forecast is for 20 guests next week, what are the salesexpected to be? PX