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Question: One critical factor that determines the success


One critical factor that determines the success of a catalog store chain is the availability of products that consumers want to buy. If a store is sold out, future sales to that customer are less likely. Accordingly, delivery trucks operating from a central warehouse regularly resupply stores. In an analysis of a chain’s operations, the general manager wanted to determine the factors that are related to how long it takes to unload delivery trucks. A random sample of 50 deliveries to one store was observed. The times (in minutes) to unload the truck, the total number of boxes, and the total weight (in hundreds of pounds) of the boxes were recorded.
a. Determine the multiple regression equation.
b. How well does the model fit the data? Explain.
c. Interpret and test the coefficients.
d. Produce a 95% interval of the amount of time needed to unload a truck with 100 boxes weighing 5,000 pounds.
e. Produce a 95% interval of the average amount of time needed to unload trucks with 100 boxes weighing 5,000 pounds.


> Refer to Exercise 17.13. a. Are the required conditions satisfied? b. Is multicollinearity a problem? If so, explain the consequences. Data from Exercise 17.13: Lotteries have become important sources of revenue for governments. Many people have critici

> Determine whether there are violations of the required conditions in the regression model used in Exercise 17.11.

> Refer to Exercise 17.10. Calculate the residuals and predicted values. a. Is the normality requirement satisfied? b. Is the variance of the error variable constant? c. Is multicollinearity a problem? Data from Exercise 17.10: Life insurance companies ar

> Health-care costs in the United States and Canada are concerns for citizens and politicians. The question is, How can we devise a system wherein people’s medical bills are covered but individuals attempt to reduce costs? An American company has come up w

> Determine whether the required conditions are satisfied in Exercise 17.9

> Are the required conditions satisfied for the regression analysis in Exercise 17.8?

> Refer to Exercise 17.7. a. Conduct an analysis of the residuals to determine whether any of the required conditions are violated. b. Does it appear that multicollinearity is a problem? c. Identify any observations that should be checked for accuracy. Da

> Are the required conditions satisfied in Exercise 17.6?

> Calculate the residuals and predicted values for the regression analysis in Exercise 17.5. a. Does the error variable appear to be normally distributed? b. Is the variance of the error variable constant? c. Is multicollinearity a problem?

> Pick any one of the previous five exercises and briefly describe why the intervals are so wide.

> Refer to Exercise 16.49. The temperature is 80 degrees. Predict with 95% confidence how far the golfer’s next drive will travel. Data from Exercise 16.49: Refer to Exercise 3.71 wherein we looked at the relationship between temperature and distance that

> Refer to Exercise 16.48. Predict with 90% confidence how definite is the intention to vote for one 50-year-old. Data from Exercise 16.48: In most presidential elections in the United States, the voter turnout is quite low, often in the neighborhood of 5

> Refer to Exercise 16.47. Estimate with 90% confidence the mean number of days watching the national news on television for the population of 70-year-olds. Data from Exercise 16.47: National news on television features commercials describing pharmaceutic

> Refer to Exercise 16.46. Use a prediction interval with 90% confidence to predict the auction selling price of one Canada 1925 nickel with a grade of 40. Data from Exercise 16.46: Refer to Exercise 3.70 where we looked at the relationship between the gr

> A study was undertaken to determine whether a drug commonly used to treat epilepsy could help alcoholics to overcome their addiction. The researchers took a sample of 103 hardcore alcoholics. Fifty-five drinkers were given topiramate and the remaining

> Refer to Exercise 16.45. Estimate with 95% confidence the mean time spent watching or reading news on the Internet for the population of people who have completed 12 years of education. Data from Exercise 16.45: Do more educated people spend more time w

> Refer to Exercise 16.18. Estimate with 95% confidence the mean percentage of defectives for workers who score 80 on the dexterity test. Data from Exercise 16.18: Although a large number of tasks in the computer industry are robotic, many operations requ

> Refer to Exercise 16.17. a. Estimate with 95% confidence the mean annual income of 6’2” (74 inches)-tall men. b. Suppose that an individual is 5’8” (68 inches). Predict with 95% confidence his annual income. Data from Exercise 16.17: One general belief

> Refer to Exercise 16.16. Predict with 95% confidence the monthly office rent in a city when the vacancy rate is 8%. Data from Exercise 16.16: An economist wanted to investigate the relationship between office rents (the dependent variable) and vacancy r

> Refer to Exercise 16.15. Predict the food budget of a family whose household income is $60,000. Use a 90% confidence level. Data from Exercise 16.15: An economist for the federal government is attempting to produce a better measure of poverty than is cu

> Refer to Exercise 16.14. Estimate with 90% confidence the mean electricity consumption for households with four occupants. Data from Exercise 16.14: In an attempt to determine the factors that affect the amount of energy used, 200 households were analyz

> Refer to Exercise 16.13. Predict with 99% confidence the price of a 1999 24-ft. Sea Ray cruiser with 400 hours of engine use. Data from Exercise 16.13: Millions of boats are registered in the United States. As is the case with automobiles, there is an a

> Refer to Exercise 16.12. Estimate with 95% confidence the mean price of 60,000 sq.ft. apartment buildings. Data from Exercise 16.12: A real estate agent specializing in commercial real estate wanted a more precise method of judging the likely selling pr

> Refer to Exercise 16.11. a. Predict with 95% confidence the percentage loss due to fire for a house that is 8 miles away from the nearest fire station. b. Estimate with 95% confidence the average percentage loss due to fire for houses that are 5 miles aw

> Refer to Exercise 16.10. Predict with 95% confidence the number of sick days for individuals who smoke on average 40 cigarettes per day. Data from Exercise 16.10: Besides their known long-term effects, do cigarettes also cause short-term illnesses such

> A professor of statistics hands back his graded midterms in class by calling out the name of each student and personally handing the exam over to its owner. At the end of the process, he notes that there are several exams left over, the result of student

> Refer to Exercise 16.9. The company has just hired a 22-year-old telemarketer. Predict with 95% confidence how long he will stay with the company. Data from Exercise 16.9: The human resource manager of a telemarketing firm is concerned about the rapid t

> Refer to Exercise 16.8. Estimate with 90% confidence the mean amount of time for 40-year-old Americans to complete the census. Data from Exercise 16.8: In 2010, the United States conducted a census of the entire country. The census is completed by mail.

> Refer to Exercise 16.7. a. Predict with 95% confidence the selling price of a 1,200 sq.ft. condominium on the 20 th floor. b. Estimate with 99% confidence the average selling price of a 1,200 sq.ft. condominium on the 15th floor. Data from Exercise 16.7

> Refer to Exercise 16.6. a. Predict with 95% confidence the memory test score of a viewer who watches a 30-second commercial. b. Estimate with 95% confidence the mean memory test score of people who watch 30-second commercials. Data from Exercise 16.6: I

> Refer to Exercise 16.5. Predict with 90% confidence the number of beers to be sold when the temperature is 75 degrees. Data from Exercise 16.5: To help determine how many beers to stock the concession manager at Yankee Stadium wanted to know how the tem

> Refer to Exercise 16.4. a. Predict with 90% confidence the number of pounds overweight for a child who watches 35 hours of television per week. b. Estimate with 90% confidence the mean number of pounds overweight for children who watch 35 hours of televi

> Estimate with 90% confidence the mean monthlynumber of housing starts when the mortgage interest rate is 7% in Exercise 16.3.

> Use the regression equation in Exercise 16.2 to predict with 90% confidence the sales when the advertising budget is $80,000.

> Will the prediction interval always be wider than the estimation interval for the same value of the independent variable? Briefly explain.

> Briefly describe the difference between predicting a value of y and estimating the expected value of y.

> Advertising is critical in the residential real estate industry. Agents are always seeking ways to increase sales through improved advertising methods. A particular agent believes that he can increase the number of inquiries (and thus the probability of

> The president of a company that manufactures drywall wants to analyze the variables that affect demand for his product. Drywall is used to construct walls in houses and offices. Consequently, the president decides to develop a regression model in which t

> Refer to Exercise 17.4. Find the coefficients of correlation of the independent variables. a. What do these correlations tell you about the independent variables? b. What do they say about the t-tests of the coefficients? Data from Exercise 17.4: The ge

> Compute the residuals and predicted values for the regression analysis in Exercise 17.3. a. Does it appear that the error variable is not normally distributed? b. Is the variance of the error variable constant? c. Is multicollinearity a problem?

> Calculate the coefficients of correlation for each pair of independent variables in Exercise 17.1. What do these statistics tell you about the independent variables and the t-tests of the coefficients?

> Compute the residuals and the predicted values for the regression analysis in Exercise 17.1. a. Is the normality requirement violated? Explain. b. Is the variance of the error variable constant? Explain.

> Pat Statsdud, a student ranking near the bottom of the statistics class, decided that a certain amount of studying could actually improve final grades. However, too much studying would not be warranted because Pat’s ambition (if that’s what one could cal

> La Quinta Motor Inns is a moderately priced chain of motor inns located across the United States. Its market is the frequent business traveler. The chain recently launched a campaign to increase market share by building new inns. The management of the ch

> Refer to Exercise 17.15. The pollster also recorded the following variables in addition to the variable DEFINITE. Number of days in previous week watching national news on television (DAYS1) Number of days in previous week watching local television news

> With voter turnout during presidential elections around 50%, a vital task for politicians is to try to predict who will actually vote. A variable used to determine who is likely to vote was created and defined as follows. DEFINITE: 1 = Definitely will no

> The MBA program at a large university is facing a pleasant problem—too many applicants. The current admissions policy requires students to have completed at least 3 years of work experience and an undergraduate degree with a B-average or better. Until 3

> Sales of a product may depend on its placement in a store. Candy manufacturers frequently offer discounts to retailers who display their products more prominently than competing brands. To examine this phenomenon more carefully, a candy manufacturer (wit

> Lotteries have become important sources of revenue for governments. Many people have criticized lotteries, however, referring to them as a tax on the poor and uneducated. In an examination of the issue, a random sample of 100 adults was asked how much th

> University students often complain that universities reward professors for research but not for teaching, and they argue that professors react to this situation by devoting more time and energy to the publication of their findings and less time and energ

> Life insurance companies are keenly interested in predicting how long their customers will live because their premiums and profitability depend on such numbers. An actuary for one insurance company gathered data from 100 recently deceased male customers.

> A developer who specializes in summer cottage properties is considering purchasing a large tract of land adjoining a lake. The current owner of the tract has already subdivided the land into separate building lots and has prepared the lots by removing so

> In Exercise 16.16, a statistics practitioner examined the relationship between office rents and the city’s office vacancy rate. The model appears to be quite poor. It was decided to add another variable that measures the state of the economy. The city’s

> Exercise 16.12 addressed the problem of determining the relationship between the price of apartment buildings and number of square feet. Hoping to improve the predictive capability of the model, the real estate agent also recorded the number of apartment

> The agronomist referred to in Exercise 16.133 believed that the amount of rainfall as well as the amount of fertilizer used would affect the crop yield. She redid the experiment in the following way. Thirty greenhouses were rented. In each, the amount of

> Are more educated (EDUC) people more likely to support government action to reduce income differences across the country differences (EQWLTH: 1 = Government should reduce income differences; 2, 3, 4, 5, 6, 7 = No government action)? Conduct a test to ans

> How does having more family members earning income (EARNRS) affect total family income (INCOME)? Conduct an analysis to determine whether there is a positive linear relationship between the two variables, and, if so, estimate with 95% confidence the aver

> A potato chip manufacturer has contracted for the delivery of 15,000,000 kilograms of potatoes. The supplier agrees to deliver the potatoes in 15,000 equal truckloads. The manufacturer suspects that the supplier will attempt to cheat him. He has the weig

> Television advertisers always want to know who is watching their televised advertising. Do older people watch more television than do younger people? Do the data provide sufficient evidence to infer that there is a positive linear relationship between ag

> Is there a linear relationship between age (AGE) and how many hours per week one works (HRS1)? Conduct a test to answer the question.

> It seems rather obvious that the longer one works the more one earns. The question is how much more one earns annually for each additional hour of work. Conduct an analysis of annual income (INCOME) and number of hours per week of work (HRS1). a. Test to

> Does television appeal to the lowest common denominator? If so, we would expect more educated people to watch less television. Is there sufficient evidence to conclude that more educated people (EDUC) watch less television (TVHOURS)?

> Conduct an analysis of the relationship between income (RINCOME) and age (AGE). Estimate with 95% confidence the average increase in income for each additional year of age.

> Does one’s income (RINCOME) affect his or her position on the question, Should the government reduce income differences between rich and poor (EQWLTH: 1 = Government should reduce income differences; 2, 3, 4, 5, 6, 7 = No government action)? Answer the q

> Refer to Exercise 3.71 wherein we looked at the relationship between temperature and distance that golf balls travel. a. Conduct a regression analysis to determine whether there is enough evidence of a positive linear relationship b. Interpret the slope

> In most presidential elections in the United States, the voter turnout is quite low, often in the neighborhood of 50%. Political workers would like to be able to predict who is likely to vote. Thus, it is important to know which variables are related to

> National news on television features commercials describing pharmaceutical drugs that treat ailments that plague older people. Apparently, the major networks believe that older people tend to watch national newscasts. The marketing manager of a drug comp

> Refer to Exercise 3.70 where we looked at the relationship between the grade of a particular coin (Canadian 1925 nickel) and its auction selling price. a. Is there sufficient evidence to conclude that the two variables are linearly related? b. Compute th

> The Scholastic Aptitude Test (SAT), which is organized by the Educational Testing Service (ETS), is important to high school students seeking admission to colleges and universities throughout the United States. A number of companies offer courses to prep

> Refer to Exercise A15.5. Suppose that in addition to varying the marketing strategy, the manufacturer also decided to advertise in one of the two media that are available: television and newspapers. As a consequence, the experiment was repeated in the fo

> Do more educated people spend more time watching or news on the Internet? To help answer the question, a statistics practitioner undertook a survey that asked a random sample of people how many years of education they had and the amount of time they spe

> Refer to Exercise 16.10. Use the t-test of the coefficient of correlation to determine whether there is evidence of a positive linear relationship between number of cigarettes smoked and the number of sick days. Data from Exercise 16.10: Besides their k

> Are food budget and household income in Exercise 16.15 linearly related? Employ the t-test of the coefficient of correlation to answer the question.

> Repeat Exercise 16.6 using the t-test of the coefficient of correlation. Is this result identical to the one you produced in Exercise 16.6?

> Repeat Exercise 16.13 using the t-test of the coefficient of correlation to determine whether there is a negative linear relationship between the number of hours of engine use and the selling price of the used boats. Data from Exercise 16.13: Millions o

> Refer to Exercise 16.18. a. Compute the coefficient of determination and describe what it tells you. b. Can we infer that aptitude test scores and percentages of nondefectives are linearly related? Data from Exercise 16.18: Although a large number of ta

> Are height and income in Exercise 16.17 positively linearly related?

> Can we infer that office rents and vacancy rates are linearly related in Exercise 16.16?

> Refer to Exercise 16.15. a. Determine the coefficient of determination and describe what it tells you. b. Conduct a test to determine whether there is evidence of a linear relationship between household income and food budget. Data from Exercise 16.15:

> Assess fit of the regression line in Exercise 16.14.

> According to the latest census, the number of households in a large metropolitan area is 425,000. The home-delivery department of the local newspaper reports that 104,320 households receive daily home delivery. To increase home-delivery sales, the market

> Is there enough evidence to infer that as the number of hours of engine use increases, the price decreases in Exercise 16.13?

> Refer to Exercise 16.12. a. Determine the standard error of estimate, and describe what this statistic tells you about the regression line. b. Can we conclude that the size and price of the apartment building are linearly related? c. Determine the coeffi

> Refer to Exercise 16.11. a. Test to determine whether there is evidence of a linear relationship between distance to the nearest fire station and percentage of damage. b. Estimate the slope coefficient with 95% confidence. c. Determine the coefficient of

> Is there evidence of a linear relationship between number of cigarettes smoked and number of sick days in Exercise 16.10?

> Refer to Exercise 16.9. Use two statistics to measure the strength of the linear association. What do these statistics tell you? Data from Exercise 16.9: The human resource manager of a telemarketing firm is concerned about the rapid turnover of the fir

> Is there enough evidence to infer that age and theamount of time needed to complete the questionnaire are linearly related in Exercise 16.8?

> Refer to Exercise 16.7. Apply the three methods of assessing the model to determine how well the linear model fits. Data from Exercise 16.7: Florida condominiums are popular winter retreats for many North Americans. In recent years, the prices have stea

> Refer to Exercise 16.6. a. What is the standard error of estimate? Interpret its value. b. Describe how well the memory test scores and length of television commercial are linearly related. c. Are the memory test scores and length of commercial linearly

> Determine whether there is evidence of a negative linear relationship between temperature and the number of beers sold at Yankee Stadium in Exercise 16.5.

> Is there evidence of a linear relationship between the number of hours of television viewing and how overweight the child is in Exercise 16.4?

> Throughout the day, many exercise shows appear on television. These usually feature attractive and fit men and women performing various exercises and urging viewers to duplicate the activity at home. Some viewers are exercisers. However, some people like

> Calculate the coefficient of determination and conducta test to determine whether a linear relationship exists between housing starts and mortgage interest in Exercise 16.3.

> Refer to Exercise 16.2. a. Determine the standard error of estimate. b. Is there evidence of a linear relationship between advertising and sales? c. Estimate 1 with 95% confidence. d. Compute the coefficient of determination and interpret this value. e.

> Suppose that you have the following data: a. Draw the scatter diagram. Does it appear that x and y are related? If so, how? b. Test to determine whether there is evidence of a linear relationship. x 3 5 2 6 1 4 y 25 110 9 250 3 71

> You have been given the following data: a. Draw the scatter diagram. Does it appear that x and y are related? If so, how? b. Test to determine whether there is evidence of a linear relationship. x 1 3 4 6 9 8 10 y 1 8 15 33 75 70 95

> Assuming that the required conditions are satisfied in Exercise 16.13, what does this tell you about the distribution of used boat prices?

> What are the required conditions for Exercise 16.8? Do these seem reasonable?

> Describe what the required conditions mean in Exercise 16.6. If the conditions are satisfied, what can you say about the distribution of memory test scores?

> Although a large number of tasks in the computer industry are robotic, many operations require human workers. Some jobs require a great deal of dexterity to properly position components into place. A large North American computer maker routinely tests ap

2.99

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