In Problem 13.10 on page 494, you used YouTube trailer views to predict movie weekend box office gross. Perform a residual analysis for these data (stored in Movie ). Based on these results, evaluate whether the assumptions of regression have been seriously violated.
> Inclusions are defects in poured metal caused by contaminants. The number of (large) inclusions in cast iron follows a Poisson distribution with a mean of 2.5 per cubic millimeter. Determine the following: a. Probability of at least one inclusion in a cu
> Suppose that X has a Poisson distribution. Determine the following probabilities when the mean of X is 4 and repeat for a mean of 0.4: a. P(X = 0) b. P(X ≤ 2) c. P(X = 4) d. P(X = 8)
> What is the difference between a confidence interval estimate of the mean response, μY|X = Xi, and a prediction interval of YX = Xi?
> When and how do you use the Durbin-Watson statistic?
> How do you evaluate the assumptions of regression analysis?
> What are the assumptions of regression analysis?
> Why should you always carry out a residual analysis as part of a regression model?
> Use the following information from a multiple regression analysis: n = 20 b1 = 4 b2 = 3 Sb1 = 1.2 Sb2 = 0.8 a. Which variable has the largest slope, in units of a t statistic? b. Construct a 95% confidence interval estimate of the population slope, b1.
> When is the explained variation (i.e., regression sum of squares) equal to 0?
> When is the unexplained variation (i.e., error sum of squares) equal to 0?
> What is the interpretation of the coefficient of determination?
> What is the interpretation of the Y intercept and the slope in the simple linear regression equation?
> Assume that you are working with the results from Problems 11.15 and 11.16. a. What is the value of the FSTAT test statistic for the interaction effect? b. What is the value of the FSTAT test statistic for the factor A effect? c. What is the value of the
> In Problem 13.10 on page 494, you used YouTube trailer views to predict movie weekend box office gross from data stored in Movie . A movie, about to be released, has 50 million YouTube trailer views. a. What is the predicted weekend box office gross? b
> In Problem 13.8 on page 494, you predicted the value of a baseball franchise, based on current revenue. The data are stored in BBValues . a. Construct a 95% confidence interval estimate of the mean value of all baseball franchises that generate $250 mil
> In Problem 13.9 on page 494, an agent for a real estate company wanted to predict the monthly rent for one-bedroom apartments, based on the size of an apartment. The data are stored in RentSilverSpring . a. Construct a 95% confidence interval estimate of
> In Problem 13.6 on page 494, a prospective MBA student wanted to predict starting salary upon graduation, based on program per-year tuition. The data are stored in FTMBA . a. Construct a 95% confidence interval estimate of the mean starting salary upon
> In Problem 13.7 on page 494, you used the plate gap on the bag-sealing equipment to predict the tear rating of a bag of coffee. The data are stored in Starbucks . a. Construct a 95% confidence interval estimate of the mean tear rating for all bags of co
> In Problem 13.4 on page 493, you used the percentage of alcohol to predict wine quality. The data are stored in VinhoVerde . For these data, SYX = 0.9369 and hi = 0.024934 when X = 10. a. Construct a 95% confidence interval estimate of the mean wine qual
> Use the following information from a multiple regression analysis: n = 25 b1 = 5 b2 = 10 Sb1 = 2 Sb2 = 8 a. Which variable has the largest slope, in units of a t statistic? b. Construct a 95% confidence interval estimate of the population slope, b1. c. A
> In Problem 13.5 on page 493, you used the summated rating of a restaurant to predict the cost of a meal. The data are stored inRestaurants . a. Construct a 95% confidence interval estimate of the mean cost of a meal for restaurants that have a summated r
> Based on a sample of n = 20, the least-squares method was used to develop the following prediction line: In addition, a. Construct a 95% confidence interval estimate of the population mean response for X = 4. b. Construct a 95% prediction interval o
> Based on a sample of n = 20, the least-squares method was used to develop the following prediction line: In addition, a. Construct a 95% confidence interval estimate of the population mean response for X = 2. b. Construct a 95% prediction interval o
> Assume that you are working with the results from Problem 11.15, and SSA = 120, SSB = 110, SSE = 270, and SST = 540. a. What is SSAB? b. What are MSA and MSB? c. What is MSAB? d. What is MSE? Problem 11.15: Consider a two-factor factorial design with th
> A survey by the Pew Research Center found that social networking is popular in many nations around the world. The file GlobalSocialMedia contains the level of social media networking (measured as the percent of individuals polled who use social networkin
> The file MobileSpeed contains the overall download and upload speeds in mbps for nine carriers in the United States. Source: Data extracted from “Best Mobile Network 2016,” bit.ly/1KGPrMm, accessed November 10, 2016. a. Compute and interpret the coeffi
> Movie companies need to predict the gross receipts of an individual movie once the movie has debuted. The following results (stored in PotterMovies ) are the first weekend gross, the U.S. gross, and the worldwide gross (in $millions) of the eight Harry P
> The file Cereals contains the calories and sugar, in grams, in one serving of seven breakfast cereals: a. Compute and interpret the coefficient of correlation, r. b. At the 0.05 level of significance, is there a significant linear relationship between
> Index funds are mutual funds that try to mimic the movement of leading indexes, such as the S&P 500 or the Russell 2000. The beta values (as described in Problem 13.49) for these funds are therefore approximately 1.0, and the estimated market models
> The volatility of a stock is often measured by its beta value. You can estimate the beta value of a stock by developing a simple linear regression model, using the percentage weekly change in the stock as the dependent variable and the percentage weekly
> In Problem 13.10 on page 494, you used YouTube trailer views to predict movie weekend box office gross from data stored in Movie . Use the results of that problem. a. At the 0.05 level of significance, is there evidence of a linear relationship between Y
> In Problem 14.8 on page 542, you used the land area of a property and the age of a house to predict the fair market value (stored in GlenCove ). a. Perform a residual analysis on your results. b. If appropriate, perform the Durbin-Watson test, using a =
> In Problem 13.9 on page 494, an agent for a real estate company wanted to predict the monthly rent for one-bedroom apartments, based on the size of the apartment. The data are stored in RentSilverSpring . Use the results of that problem. a. At the 0.05 l
> In Problem 13.8 on page 494, you used annual revenues to predict the value of a baseball franchise. The data are stored in BBValues . Use the results of that problem. a. At the 0.05 level of significance, is there evidence of a linear relationship betwee
> Consider a two-factor factorial design with three levels for factor A, three levels for factor B, and four replicates in each of the nine cells. a. How many degrees of freedom are there in determining the factor A variation and the factor B variation? b.
> In Problem 13.7 on page 494, you used the plate gap in the bag-sealing equipment to predict the tear rating of a bag of coffee. The data are stored in Starbucks . Use the results of that problem. a. At the 0.05 level of significance, is there evidence of
> In Problem 13.6 on page 494, a prospective MBA student wanted to predict starting salary upon graduation, based on program per-year tuition. The data are stored in FTMBA . Use the results of that problem. a. At the 0.05 level of significance, is there ev
> In Problem 13.5 on page 493, you used the summated rating of a restaurant to predict the cost of a meal. The data are stored in Restaurants . a. At the 0.05 level of significance, is there evidence of a linear relationship between the summated rating of
> In Problem 13.4 on page 493, you used the percentage of alcohol to predict wine quality. The data are stored in VinhoVerde . From the results of that problem, b1 = 0.5624 and Sb1 = 0.1127. a. At the 0.05 level of significance, is there evidence of a line
> You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 20, you determine that SSR = 60 and SSE = 40. a. What is the value of FSTAT? b. At the a = 0.05 level of significance, what i
> You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 18, you determine that b1 = +4.5 and Sb1 = 1.5. a. What is the value of tSTAT? b. At the α = 0.05 level of significance, wh
> You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 10, you determine that r = 0.80. a. What is the value of the t test statistic tSTAT? b. At the α = 0.05 level of significan
> The owners of a chain of ice cream stores have the business objective of improving the forecast of daily sales so that staffing shortages can be minimized during the summer season. As a starting point, the owners decide to develop a simple linear regress
> In Problem 14.7 on page 542, you used the weekly staff count and remote engineering hours to predict standby hours (stored in Nickels26Weeks ). a. Perform a residual analysis on your results. b. If appropriate, perform the Durbin-Watson test, using a = 0
> A transportation strategist wanted to compare the traffic congestion levels across four continents: Asia, Europe, North America, and South America. The file CongestionLevel contains congestion level, defined as the increase (%) in overall travel time whe
> A mail-order catalog business that sells personal computer supplies, software, and hardware maintains a centralized warehouse for the distribution of products ordered. Management is currently examining the process of distribution from the warehouse and h
> In Problem 13.7 on page 494 concerning the bag-sealing equipment at Starbucks, you used the plate gap to predict the tear rating. a. Is it necessary to compute the Durbin-Watson statistic in this case? Explain. b. Under what circumstances is it necessary
> The residuals for 15 consecutive time periods are as follows: a. Plot the residuals over time. What conclusion can you reach about the pattern of the residuals over time? b. Compute the Durbin-Watson statistic. At the 0.05 level of significance, is the
> The residuals for 10 consecutive time periods are as follows: a. Plot the residuals over time. What conclusion can you reach about the pattern of the residuals over time? b. Based on (a), what conclusion can you reach about the autocorrelation of the r
> In Problem 13.8 on page 494, you used annual revenues to predict the value of a baseball franchise. Perform a residual analysis for these data (stored in BBValues ). Based on these results, evaluate whether the assumptions of regression have been serious
> In Problem 13.9 on page 494, an agent for a real estate company wanted to predict the monthly rent for one-bedroom apartments, based on the size of the apartments. Perform a residual analysis for these data (stored in RentSilverSpring ). Based on these r
> In Problem 13.6 on page 494, a prospective MBA student wanted to predict starting salary upon graduation, based on program per-year tuition. Perform a residual analysis for these data (stored in FTMBA ). Based on these results, evaluate whether the assum
> In Problem 14.6 on page 542, you used full-time voluntary turnover (%), and total worldwide revenue ($billions) to predict number of full-time jobs added (stored in BestCompanies ). a. Perform a residual analysis on your results. b. If appropriate, perfo
> In Problem 14.6 on page 542, you used full-time voluntary turnover (%) and total worldwide revenue ($billions) to predict number of full-time jobs added (stored in BestCompanies ). Using the results from that problem, a. determine whether there is a sig
> For this problem, use the following multiple regression equation: a. Interpret the meaning of the slopes. b. Interpret the meaning of the Y intercept. Y; = 50 – 2X1; + 7X2;
> In Problem 13.7 on page 494, you used the plate gap on the bag-sealing equipment to predict the tear rating of a bag of coffee. Perform a residual analysis for these data (stored in Starbucks ). Based on these results, evaluate whether the assumptions of
> In Problem 13.4 on page 493, you used the percentage of alcohol to predict wine quality. Perform a residual analysis for these data (stored in VinhoVerde ). Evaluate whether the assumptions of regression have been seriously violated.
> In Problem 13.5 on page 493, you used the summated rating to predict the cost of a restaurant meal. Perform a residual analysis for these data (stored in Restaurants ). Evaluate whether the assumptions of regression have been seriously violated.
> The following results show the X values, residuals, and a residual plot from a regression analysis: Is there any evidence of a pattern in the residuals? Explain. X Residuals 0.70 Residual Plot 2 1.58 2.0 1.03 0.33 1.5 5 -0.39 -0.67 1.0 7 -0.56 0.65
> The following results provide the X values, residuals, and a residual plot from a regression analysis: Is there any evidence of a pattern in the residuals? Explain. X Residuals 1 0.70 Residual Plot 2 -0.78 3.0 3 1.03 4 0.33 2.5 2.39 2.0 -0.67 7 0.1
> In Problem 13.10 on page 494, you used YouTube trailer views to predict movie weekend box office gross (stored in Movie ). Using the results of that problem, a. determine the coefficient of determination, r2, and interpret its meaning. b. determine the s
> In Problem 13.9 on page 494, an agent for a real estate company wanted to predict the monthly rent for one-bedroom apartments, based on the size of the apartment (stored in RentSilverSpring ). Using the results of that problem, a. determine the coefficie
> In Problem 13.8 on page 494, you used annual revenues to predict the value of a baseball franchise (stored in BBValues ). Using the results of that problem, a. determine the coefficient of determination, r2, and interpret its meaning. b. determine the s
> In Problem 13.7 on page 494, you used the plate gap on the bag-sealing equipment to predict the tear rating of a bag of coffee (stored in Starbucks ). Using the results of that problem, a. determine the coefficient of determination, r2, and interpret it
> A pet food company has a business objective of expanding its product line beyond its current kidney and shrimp-based cat foods. The company developed two new products, one based on chicken liver and the other based on salmon. The company conducted an exp
> In Problem 13.6 on page 494, a prospective MBA student wanted to predict starting salary upon graduation, based on program per-year tuition (stored in FTMBA ). Using the results of that problem, a. determine the coefficient of determination, r2, and inte
> In Problem 13.5 on page 493, you used the summated rating to predict the cost of a restaurant meal (stored in Restaurants ). a. Determine the coefficient of determination, r2, and interpret its meaning. b. Determine the standard error of the estimate. c.
> In Problem 13.4 on page 493, the percentage of alcohol was used to predict wine quality (stored in VinhoVerde ). For those data, SSR = 21.8677 and SST = 64.0000. a. Determine the coefficient of determination, r2, and interpret its meaning. b. Determine t
> If SSR = 120, why is it impossible for SST to equal 110?
> If SSE = 10 and SSR = 30, compute the coefficient of determination, r2, and interpret its meaning.
> If SSR = 66 and SST = 88, compute the coefficient of determination, r2, and interpret its meaning.
> If SSR = 36 and SSE = 4, determine SST and then compute the coefficient of determination, r2, and interpret its meaning.
> How do you interpret a coefficient of determination, r2, equal to 0.80?
> A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use YouTube trailer views as a predictor. For each of 66 movies, the YouTube trailer view count, the number of YouTube trailer views
> Brand valuations are critical to CEOs, financial and marketing executives, security analysts, institutional investors, and others who depend on well-researched, reliable information needed for assessments and comparisons in decision making. Millward Brow
> An agent for a residential real estate company in a suburb located outside of Washington, DC, has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward that goal, the agent would like to use the si
> The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The file BBValues represents the value in 2017 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises.
> Starbucks Coffee Co. uses a data-based approach to improving the quality and customer satisfaction of its products. When survey data indicated that Starbucks needed to improve its package-sealing process, an experiment was conducted to determine the fact
> Is an MBA a golden ticket? Pursuing an MBA is a major personal investment. Tuition and expenses associated with business school programs are costly, but the high costs come with hopes of career advancement and high salaries. A prospective MBA student wou
> Zagat’s publishes restaurant ratings for various locations in the United States. The file Restaurants contains the Zagat rating for food, décor, service, and the cost per person for a sample of 100 restaurants located in the center of New York City and i
> The production of wine is a multibillion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data were collected from red wine variants of Portuguese “Vinho Verde” wine. Source: Data extracted from Cort
> Fitting a straight line to a set of data yields the following prediction line: a. Interpret the meaning of the Y intercept, b0. b. Interpret the meaning of the slope, b1. c. Predict the value of Y for X = 6. Î, = 16 – 0.5X;
> If the values of X in Problem 13.1 range from 2 to 25, should you use this model to predict the mean value of Y when X equals a. 3? b. -3? c. 0? d. 24?
> Fitting a straight line to a set of data yields the following prediction line: a. Interpret the meaning of the Y intercept, b0. b. Interpret the meaning of the slope, b1. c. Predict the value of Y for X = 3. Î; = 2 + 5X;
> QSR reports on the largest quick-serve and fast-casual brands in the United States. The file FastFoodChain contains the food segment (burger, chicken, sandwich or pizza/pasta) and U.S. mean sales per unit ($ thousands) for each of 37 quick-service brands
> Use the following contingency table: a. Compute the expected frequency for each cell. b. Compute χ2STAT. Is it significant at α = 0.05? A B C Total 1 10 30 50 90 2 40 45 50 135 Total 50 75 100 225
> Consider a contingency table with two rows and five columns. a. How many degrees of freedom are there in the contingency table? b. Determine the critical value for α = 0.05. c. Determine the critical value for α = 0.01.
> Does co-browsing have positive effects on the customer experience? Co-browsing refers to the ability to have a contact center agent and customer jointly navigate an application (e.g., web page, digital document, or mobile application) on a real time basi
> A glass manufacturing company wanted to investigate the effect of zone 1 lower temperature (630 vs. 650) and zone 3 upper temperature (695 vs. 715) on the roller imprint of glass. The results stored in Glass2 were as follows: Source: K. Kumar and S. Y
> What social media tools do marketers commonly use? A survey by Social Media Examiner of B2B marketers (marketers that focus primarily on attracting businesses) and B2C marketers (marketers that primarily target consumers) reported that 267 (81%) of B2B m
> The Society for Human Resource Management (SHRM) collaborated with Globoforce on a series of organizational surveys with the goal of identifying challenges that HR leaders face and what strategies help them conquer those challenges. A 2016 survey indicat
> Are you an impulse shopper? A survey of 500 grocery shoppers indicated that 29% of males and 40% of females make an impulse purchase every time they shop. Source: Data extracted from Women shoppers are impulsive while men snap up bargains, available at b
> Does Cable Video on Demand (VOD D4+) increase ad effectiveness? A 2015 VOD study compared general TV and VOD D4+ audiences after viewing a brand ad. Whether the viewer indicated that the ad made them want to visit the brand website was collected and orga
> An Ipsos poll asked 1,004 adults “If purchasing a used car made certain upgrades or features more affordable, what would be your preferred luxury upgrade?” The results indicated that 9% of the males and 14% of the females answered window tinting. Source
> Use the following contingency table: a. Compute the expected frequency for each cell. b. Compute χ2STAT. Is it significant at α = 0.05? A B Total 1 20 30 50 2 30 20 50 Total 50 50 100
> Use the following contingency table: a. Compute the expected frequency for each cell. b. Compare the observed and expected frequencies for each cell. c. Compute χ2STAT. Is it significant at α = 0.05? A B Total 1 20 Total
> The following ANOVA summary table is for a multiple regression model with two independent variables: a. Determine the regression mean square (MSR) and the mean square error (MSE). b. Compute the overall FSTAT test statistic. c. Determine whether the
> Determine the critical value of χ2 with 1 degree of freedom in each of the following circumstances: a. α = 0.05 b. α = 0.025 c. α = 0.01
> Determine the critical value of χ2 with 1 degree of freedom in each of the following circumstances: a. α = 0.01 b. α = 0.005 c. α = 0.10
> A glass manufacturing company wanted to investigate the effect of breakoff pressure and stopper height on the percentage of breaking off chips. The results, stored in Glass1 , were as follows: Source: K. Kumar and S. Yadav, “Breakth
