Essentials Of Statistics For Business & Economics
9th Edition
ISBN: 9780357045435
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: South-Western College Pub
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Chapter 15.3, Problem 15E
a.
To determine
Compute
Interpret the results.
b.
To determine
Explain whether the multiple regression results is preferable when television advertising was the only one predictor variable with
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In exercise 5, the owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue ( y) as a function of television advertising (x1) and newspaperadvertising (x2). The estimated regression equation wasThe computer solution provided SST = 25.5 and SSR = 23.435.
yˆ = 83.2 + 2.29x1 + 1.30x2
a. Compute and interpret R2 and .b. When television advertising was the only independent variable, R2 + .653 and R2a=.595. Do you prefer the multiple regression results? Explain
Which of the multivariate regression parameters listed below would be best interpreted as: the predicted value on the dependent variable when all of the independent variables in the model are equal to zero.
a
b1
X1
R2
a) For United States, provide data for the variables below over the years 1993 – 2007:
(i) Net migration rate (per 1,000 population)
(ii) Total fertility rate (live births per woman)
(iii)Unemployment, general level (Thousands)
(iv) Wages
(v) Life expectancy at birth for both sexes combined (years)
Data can be obtained from the UN database http://data.un.org/Explorer.aspx
Using R-Studio, estimate a regression equation to determine the effect of unemployment, general level, wages and life expectancy at birth for both sexes on the net migration rate. (All codes and regression output should be provided).(i) Write down the regression equation. (ii) Interpret the coefficients and determine which of the individual coefficients in theregression model are statistically significant. In responding, construct and test anyappropriate hypothesis. (iii) Interpret the coefficient of determination. (iv) Using the 10% level of significance, determine and discuss whether the overallregression equation…
Chapter 15 Solutions
Essentials Of Statistics For Business & Economics
Ch. 15.2 - The estimated regression equation for a model...Ch. 15.2 - Consider the following data for a dependent...Ch. 15.2 - 3. In a regression analysis involving 30...Ch. 15.2 - A shoe store developed the following estimated...Ch. 15.2 - Theater Revenue. The owner of Showtime Movie...Ch. 15.2 - NFL Winning Percentage. The National Football...Ch. 15.2 - Rating Computer Monitors. PC Magazine provided...Ch. 15.2 - Scoring Cruise Ships. The Condé Nast Traveler Gold...Ch. 15.2 - House Prices. Spring is a peak time for selling...Ch. 15.2 - Baseball Pitcher Performance. Major League...
Ch. 15.3 - In exercise 1, the following estimated regression...Ch. 15.3 - In exercise 2, 10 observations were provided for a...Ch. 15.3 - 13. In exercise 3, the following estimated...Ch. 15.3 - In exercise 4, the following estimated regression...Ch. 15.3 - Prob. 15ECh. 15.3 - 16. In exercise 6, data were given on the average...Ch. 15.3 - Quality of Fit in Predicting House Prices. Revisit...Ch. 15.3 - R2 in Predicting Baseball Pitcher Performance....Ch. 15.5 - In exercise 1, the following estimated regression...Ch. 15.5 - Refer to the data presented in exercise 2. The...Ch. 15.5 - The following estimated regression equation was...Ch. 15.5 - Testing Significance in Shoe Sales Prediction. In...Ch. 15.5 - Testing Significance in Theater Revenue. Refer to...Ch. 15.5 - Testing Significance in Predicting NFL Wins. The...Ch. 15.5 - Auto Resale Value. The Honda Accord was named the...Ch. 15.5 - Testing Significance in Baseball Pitcher...Ch. 15.6 - In exercise 1, the following estimated regression...Ch. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - 34. Management proposed the following regression...Ch. 15.7 - Repair Time. Refer to the Johnson Filtration...Ch. 15.7 - Extending Model for Repair Time. This problem is...Ch. 15.7 - Pricing Refrigerators. Best Buy, a nationwide...Ch. 15.9 - In Table 15.12 we provided estimates of the...Ch. 15 - 49. The admissions officer for Clearwater College...Ch. 15 - 50. The personnel director for Electronics...Ch. 15 - A partial computer output from a regression...Ch. 15 - Analyzing College Grade Point Average. Recall that...Ch. 15 - Analyzing Job Satisfaction. Recall that in...Ch. 15 - Analyzing Repeat Purchases. The Tire Rack,...Ch. 15 - Zoo Attendance. The Cincinnati Zoo and Botanical...Ch. 15 - Mutual Fund Returns. A portion of a data set...Ch. 15 - Gift Card Sales. For the holiday season of 2017,...Ch. 15 - Consumer Research, Inc., is an independent agency...Ch. 15 - Matt Kenseth won the 2012 Daytona 500, the most...Ch. 15 - When trying to decide what car to buy, real value...
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Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forward(a) For United States, provide data for the variables below over the years 1993 – 2007: (i) Net migration rate (per 1,000 population) (ii) Total fertility rate (live births per woman) (iii)Unemployment, general level (Thousands) (iv) Wages (v) Life expectancy at birth for both sexes combined (years) Data can be obtained from the UN database http://data.un.org/Explorer.aspx Using R-Studio, estimate a regression equation to determine the effect of unemployment, general level, wages and life expectancy at birth for both sexes on the net migration rate. (All codes and regression output should be provided).(b) Using R-Studio redo the regression analysis with the total fertility rate as an additionalindependent variable. (All codes and regression output should be provided).(i) Write down the regression equation. (ii) Use the 5% level of significance, determine and discuss whether the total fertilityrate has a significant impact on the net migration rate in your assigned country.…arrow_forward(a) For United States, provide data for the variables below over the years 1993 – 2007: (i) Net migration rate (per 1,000 population) (ii) Total fertility rate (live births per woman) (iii)Unemployment, general level (Thousands) (iv) Wages (v) Life expectancy at birth for both sexes combined (years) Data can be obtained from the UN database http://data.un.org/Explorer.aspx Using R-Studio, estimate a regression equation to determine the effect of unemployment, general level, wages and life expectancy at birth for both sexes on the net migration rate. (All codes and regression output should be provided). (iv) Using the 10% level of significance, determine and discuss whether the overall regression equation is statistically significant. In responding, construct and test any appropriate hypothesis. (v) Determine and interpret the confidence interval for the independent variable(s).arrow_forward
- In exercise 4, the following estimated regression equation relating sales to inventory investment and advertising expenditures was given.The data used to develop the model came from a survey of 10 stores; for these dataSST = 16,000 and SSR =12,000. yˆ = 25 + 10x1 + 8x2 a. Compute SSE, MSE, and MSR.b. Use an F test and a .05 level of significance to determine whether there is a relationship among the variables.arrow_forwardConsider the following regression analysis between sales (Y in $1,000) and social media advertising (X in dollars).Ŷ = 55,000 + 7XThe regression equation implies that an ________. Multiple Choice increase of $7 in advertising is associated with an increase of $7,000 in sales increase of $1 in advertising is associated with an increase of $7 in sales increase of $1 in advertising is associated with an increase of $62,000 in sales increase of $1 in advertising is associated with an increase of $7,000 in salesarrow_forwardThe following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. a. Fit the regression line y = a+bx to the data and interpret the results. b. Use the regression equation to determine the SY16C grade for a college student who scored60 on their achievement test. What would their SY16C grade bearrow_forward
- The marketing manager of a supermarket chain would like to determine the effect of shelf spaceon the sales of pet food. A random sample of 10 stores was selected, and the results are presentedbelow. Store shelf space in cm weekly sales in thousand pesos 1 45 18 2 45 21 3 75 15 4 80 18 5 95 23 6 100 26 7 135 22 8 140 27 9 185 25 10 190 28 d. Using the estimated simple linear regression equation Y=15.6414+0.0611X, estimate the weekly sales when theshelf space is 230cm? 250cm? e. Compute the coefficient of determination and interpret its value.arrow_forwardA seafood-sales manager collected data on the maximum daily temperature, T, and the daily revenue from salmon sales, R, using sales receipts for 30 days selected at random. Using the data, the manager conducted a regression analysis and found the least-squares regression line to be Rˆ=126+2.37T. A hypothesis test was conducted to investigate whether there is a linear relationship between maximum daily temperature and the daily revenue from salmon sales. The standard error for the slope of the regression line is SEb1=0.65. Assuming the conditions for inference have been met, which of the following is closest to the value of the test statistic for the hypothesis test? t=0.274 A t=0.65 B t=1.54 C t=3.65 D t=193.85 Earrow_forwardIn a statistics course, a linear regression equation was computed to predict the final exam score from the score on the midterm exam. The equation of the least‑squares regression line was ?̂ =10+0.9?, where ?y represents the final exam score and ?x is the midterm exam score. Suppose Joe scores an 80 on the midterm exam. What would be the predicted value of his score on the final exam?arrow_forward
- (a) For United States, provide data for the variables below over the years 1993 –2007:(i) Net migration rate (per 1,000 population)(ii) Total fertility rate (live births per woman)(iii)Unemployment, general level (Thousands)(iv) Wages(v) Life expectancy at birth for both sexes combined (years)Data can be obtained from the UN database http://data.un.org/Explorer.aspxUsing R-Studio, estimate a regression equation to determine the effect of unemployment,general level, wages and life expectancy at birth for both sexes on the net migration rate.(All codes and regression output should be provided).(i) Write down the regression equation. (ii) Interpret the coefficients and determine which of the individual coefficients in theregression model are statistically significant. In responding, construct and test anyappropriate hypothesis. (iii) Interpret the coefficient of determination.arrow_forwardThe table contains data on vehicle speed (h) and fuel consumption (lt / 100km) of 5 randomly selected vehicles. Estimate the average fuel consumption of a vehicle traveling at 45 km / h using the simple linear regression equation between vehicle speed and fuel consumption. Speed 55 60 65 70 75 Consumption 11 10 9 8 7 Please choose one: a. 6 b. 5 c. 13 D. 8arrow_forwardThe owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x 2). The estimated regression equation was Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 97 6 1.5 91 3 2 95 5 2.5 93 3.5 2.5 96 4 4.3 94 4.5 2.3 95 3.5 4.2 95 4 3.5 ŷ = 82.5 + 2.01 x 1 + 1.26 x 2The computer solution provided SST = 24 and SSR = 22.876. Compute R 2 and R a 2 (to 3 decimals). R 2 R a 2 When television advertising was the only independent variable, R 2 = 0.551 and R a 2 = 0.476. Are the multiple regression analysis results preferable?arrow_forward
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