Purchasing agent Angela Rodriguez reported the number of sales calls she received from suppliers on each of the past 14 days. Compute the variance for her daily calls during the 14-day period. Treat the data as a sample Number of calls and the number of days Calls (x) 4 50 6 7 8 Number of days f(x) 1 3 4 4 2

Purchasing agent Angela Rodriguez reported the number of sales calls she received from suppliers on each of the past 14 days. Compute the variance for her daily calls during the 14-day period. Treat the data as a sample Number of calls and the number of days Calls (x) 4 50 6 7 8 Number of days f(x) 1 3 4 4 2

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.3: Simple Regression Models

Problem 6P: Do the sales prices of houses in a given community vary systematically with their sizes (as measured...

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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?
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 classified department of a monthly magazine has used a combination of quantitative and qualitative methods to forecast sales of advertising space. Results over a 20-month period are as follows: Month Error Month Error 1 —8 11 1 2 —2 12 6 3 4 13 4 7 14 4 5 9 15 1 6 5 16 —2 7 0 17 —4 8 —3 18 —8 9 -9 19 —5 10 —4 20 —1 a. Compute a tracking signal for months 11 through 20. Compute
The classified department of a monthly magazine has used a combination of quantitative and qualitative methods to forecast sales of advertising space. Results over a 20-month period are as follows:Month Error1 −8 2 −2 3 4 4 7 5 9 6 5 7 0 8 −3 9 −9 10 −4 11 1 12 6 13 8 14 4 15 1 16 −2 17 −4 18 −8 19 −5 20 −1 a. Compute a tracking signal for months 11 through 20. Compute an initial value of MAD for month 11, and then update it for each month using exponential smoothing with α = .1. What can you conclude? Assume limits of ± 4.b. Using the first half of the data, construct a control chart with 2s limits. What can you conclude?c. Plot the last 10 errors on the control chart. Are the errors random? What is the implication of this?
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?
Prior to conducting double exponential smoothing a simple linear regression is conducted and the trend equation is Y=42+38.3t, so the smoothed constant process value should be C0=38.3 and the smoothed trend value should be T0=42.? TRUE OR FALSE?
The time to deliver packaged containers by a logistics company is found fromsamples of size 4. The mean and standard deviation of delivery times is estimated tobe 140 hours and 6 hours, respectively.(a) Find the 2 sigma and 3 sigma control limits for the average delivery time.(b) Explain a type I and type II error specifically in this context.(c) If the mean delivery time shifts to 145 hours, what is the probability of notdetecting this by the second sample after the shift?(d) What is the ARL? Explain
Rajan wanted a radio from Jacky's. It appears that Rajan is particularly interested in purchasing a Radio from the inexpensive retailer's sales manager for consumer electronics. He tells Jacky, the salesperson at the inexpensive store where he thinks he'll get the best deal, that his old radio died and he wants to listen to his favourite tunes. He wants a replacement radio as quickly as possible. In three and a half weeks, Rajan's favourite model will be 10% off.He suspects Rajan won't wait and will find another job. Jacky will earn less on the lowered price. He thinks that telling Rajan of the sale makes little sense.When Jacky tells Rajan that the radio set he wants is no longer available and won't be for another week, Rajan is enraged. Fearing losing the business, Jacky begs his sales manager, Michelle, to speed up delivery. Michelle says it's impossible and suggests Jacky tell Rajan the store can get the set in 24 hours and sell him the demo model. Michelle says the sample is new…
The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week of Pints Used August 31 360 September 7 370 September 14 412 September 21 383 September 28 371 October 5 371 a) The forecasted demand for the week of October 12 using a 3-week moving average= {__] Pints (round your response to two decimal places).
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The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1012 872 895 1078 1235 1172 Temperature (°F) 81.9 76.3 78.4 84 87.2 88.4 What is the regression equation? y= +. x What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best-predicted temperature when a bug is chirping at 3000 chirps per minute is ? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an…