Intro STATS, Books a la Carte Plus New Mystatlab with Pearson Etext -- Access Card Package
4th Edition
ISBN: 9780321869852
Author: Richard D. De Veaux
Publisher: PEARSON
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Chapter 8, Problem 3E
To determine
The fitted
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You have been hired to help a large supermarket retail chain. they are trying to understand how aisle location of specialty pet food - whether specialty pet food is placed at the front or back of the aisle, and shelf space allocated to it (in square feet) affect its sales. An data analyst colleague provided the following regression analysis.
Sales: weekly sales in $ (dependent variable)
aisle location: 1 if the product was placed at the front of the aisle; 0 if the product was placed at the back of the aisle
Shelf space: shelf space occupied by specialty pet food (in square feet)
Use the attached regression analysis to answer the following questions:
Question A.
If two stores A and B had the same shelf space allocated to specialty pet food but store A placed this product at the front of the aisle whereas store B placed this product at the back of the aisle, which of these two stores would have higher sales of this specialty pet food? A or B?
Question B
Suppose that you have…
Mark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for
their line of company speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the
main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for its particular market.
Pertinent information was collected by an extensive marketing project that lasted over the past 12 years and was reduced to the data
that follow:
YEAR
1
2
3
4
5
6
7
B
9
10
11
12
UNIT SALES
(THOUSANDS)
398
698
898
y bar
1,304
1,163
1,195
898
1,200
982
1,235
875
811
PRICE $ PER
UNIT
283
209
213
220
209
200
220
209
230
213
216
243
ADVERTISING
($000)
621
821
1,200
1,405
1,210
1,304
875
1,200
691
875
691
691
a. Perform a regression analysis based on these data using Excel.
Note: Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.
Price
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Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks.
The research question is
How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)?
Conduct a multiple regression analysis to answer the following questions:
What is the regression equation for all the predictors?
Write a results section based on your analysis that answers the research question.
Chapter 8 Solutions
Intro STATS, Books a la Carte Plus New Mystatlab with Pearson Etext -- Access Card Package
Ch. 8.3 - Each of these scatterplots shows an unusual point....Ch. 8.3 - Prob. 2JCCh. 8.3 - Prob. 3JCCh. 8 - Credit card spending An analysis of spending by a...Ch. 8 - Prob. 2ECh. 8 - Prob. 3ECh. 8 - Prob. 4ECh. 8 - Prob. 5ECh. 8 - Prob. 6ECh. 8 - Prob. 7E
Ch. 8 - Prob. 8ECh. 8 - Prob. 9ECh. 8 - Prob. 10ECh. 8 - Skinned knees There is a strong correlation...Ch. 8 - Prob. 12ECh. 8 - Prob. 13ECh. 8 - Average GPA An athletic director proudly states...Ch. 8 - Prob. 15ECh. 8 - Prob. 16ECh. 8 - Good model? In justifying his choice of a model, a...Ch. 8 - Prob. 20ECh. 8 - Movie dramas Heres a scatterplot of the production...Ch. 8 - Prob. 22ECh. 8 - Prob. 23ECh. 8 - Prob. 24ECh. 8 - Unusual points Each of these four scatterplots...Ch. 8 - More unusual points Each of the following...Ch. 8 - Prob. 27ECh. 8 - Prob. 28ECh. 8 - Prob. 29ECh. 8 - Whats the effect? A researcher studying violent...Ch. 8 - Reading To measure progress in reading ability,...Ch. 8 - Prob. 32ECh. 8 - Heating After keeping track of his heating...Ch. 8 - Speed How does the speed at which you drive affect...Ch. 8 - Prob. 35ECh. 8 - Prob. 36ECh. 8 - Prob. 37ECh. 8 - Prob. 38ECh. 8 - Prob. 39ECh. 8 - Prob. 40ECh. 8 - Prob. 41ECh. 8 - Prob. 42ECh. 8 - 43. Marriage age 2010 revisited Suppose you wanted...Ch. 8 - Prob. 44ECh. 8 - Prob. 45ECh. 8 - Prob. 46ECh. 8 - Prob. 47ECh. 8 - Prob. 48E
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardLife Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardDemand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00arrow_forward
- For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardFor the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.arrow_forward
- Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. The research question is How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)? Conduct a multiple regression analysis to answer the following questions: What is the relationship of age, number of years, and social support with work stress? Is the regression significant? If yes, what does it indicate?arrow_forwardMark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of stereo speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for its particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 12 years and was reduced to the data that follow: YEAR 123456789 10 11 12 UNIT SALES (THOUSANDS) 396 696 896 1,285 1,155 1,186 896 1,118 985 1,334 926 820 PRICE $/UNIT 282 219 206 210 219 209 218 206 220 206 226 236 ADVERTISING ($000) 600 829 1,118 1,413 1,214 1,285 907 1,118 708 907 708 682 a. Perform a regression analysis based on these data using Excel. (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.)arrow_forwardBowling Corporation wants to know how closely its current cost driver is correlated with its monthly operating costs. The managerial accountant runs a regression analysis using a statistical software program and produces the following data: Intercept Coefficient = 12,200,567 X Variable 1 Coefficient = 95.65 R-square= 0.8574 What is the Bowling Corporation's monthly cost equation? OA. y $95.65x + $12,200,567 OB. y $95.65x + $8.574 O c. y = $0.8574x + $12,200,567 O D. y = $12,200,567x + $8,574 ---arrow_forward
- Mark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of stereo speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for their particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 10 years and was reduced to the data that follow: YEAR SALES/UNIT (THOUSANDS) PRICE $/UNIT ADVERTISING ($000) 1998 395 278 605 1999 695 219 831 2000 895 216 1,104 2001 1,286 207 1,404 2002 1,147 219 1,203 2003 1,180 193 1,286 2004 895 222 884 2005 1,104 202 1,104 2006 974 220 696 2007 1,238 216 884 2008 884 220 696 2009 804 247 696arrow_forwardBill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. The research question is How accurately can work stress be predicted from linear combination of the predictors (age, social support, number of years at the workplace)? Conduct a multiple regression analysis to answer the following questions: State the hypothesis for this study.arrow_forwardsee attachmentarrow_forward
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