Basic Business Statistics, Student Value Edition
14th Edition
ISBN: 9780134685113
Author: Mark L. Berenson, David M. Levine, David F. Stephan, Kathryn Szabat
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Textbook Question
Chapter 13, Problem 28PS
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 assumptions of regression have been seriously violated.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
Suppose you wanted to test whether or not the payoff to an additional year of education was the same for men and women in the STEM majors. How would you set up your regression analysis in this case
a) Give a practical interpretation of the y-intercept of the regression line. b) What is the best-predicted value for the median hourly wage gain for the fifteenth year of schooling? c) The actual wage gain for the fifteenth year of schooling was 14%. How close was the predicted wage gain present to the actual value, i.e. what is the residual?
If a scatterplot is created in excel, and a line of regression is fit along with a derived functional form, what does it mean to describe and interpret them? What conclusions would be made about relationships between two recorded variables?
Chapter 13 Solutions
Basic Business Statistics, Student Value Edition
Ch. 13 - Prob. 1PSCh. 13 - If the values of X in Problem 13.1 from 2 to 25,...Ch. 13 - Fitting a straight line to a set data yields the...Ch. 13 - The production of wine is a multibillion-dollar...Ch. 13 - Zagat’s publisher restaurant rating for various...Ch. 13 - Is an MBA a golden ticket? Pursuing an MBA is a...Ch. 13 - Starbucks Coffee Co. uses a data-based approach to...Ch. 13 - The value of a sports franchise is directly...Ch. 13 - An agent for a residential real estate company in...Ch. 13 - A box office analyst seeks to predict opening...
Ch. 13 - How do you interpret a coefficient by of...Ch. 13 - If SSR= 36 and SSE=4, determine SST and then...Ch. 13 - If SSR=66 and SST=88, Compute the coefficient of...Ch. 13 - If SSE= 10 and SSR=30, compute the coefficient of...Ch. 13 - If SSR=120, Why is it impossible for SST to equal...Ch. 13 - In problem 13.4 on page 493, the percentage of...Ch. 13 - In problem 13.5 on page 493, you used the summated...Ch. 13 - In Problem 13.6 on page 494, a prospective MBA...Ch. 13 - In Problem 13.7 on page 494, you used the plate...Ch. 13 - In problem 13.8 on page 494, you used annual...Ch. 13 - In problem 13.9 on page 494, an agent for a real...Ch. 13 - In problem 13.10 on page 494, you used You tube...Ch. 13 - The following results provide the X Values,...Ch. 13 - The following results show the X Values,...Ch. 13 - In problem 13.5 on page 493, you used the summated...Ch. 13 - In problem 13.4 on page 493, you used the...Ch. 13 - In problem 13.7 on page 494, you used the plate...Ch. 13 - In problem 13.6 on page 494, a prospective MBA...Ch. 13 - In problem 13.9 on page 494, an agent for a real...Ch. 13 - Prob. 30PSCh. 13 - Prob. 31PSCh. 13 - The residuals for 10 consecutive time periods are...Ch. 13 - The residuals for 15 consecutive time periods are...Ch. 13 - In Problem 13.7 on page 494 concerning the...Ch. 13 - What is the relationship between the price of...Ch. 13 - Prob. 36PSCh. 13 - A freshly brewed shot of espresso has three...Ch. 13 - The owners of a chain of ice cream stores have the...Ch. 13 - You are testing the null hypothesis that there is...Ch. 13 - Prob. 40PSCh. 13 - Prob. 41PSCh. 13 - In problem 13.4 on page 493, you used the...Ch. 13 - Prob. 43PSCh. 13 - In problem 13.6 on page 494, a prospective MBA...Ch. 13 - In Problem 13.7 on page 494, you used the plate...Ch. 13 - Prob. 46PSCh. 13 - In Problem 13.9 on page 494, an agent for a real...Ch. 13 - In Problem 13.10 on page 494, you used you used...Ch. 13 - The volatility of a stock is often measured by its...Ch. 13 - Prob. 50PSCh. 13 - Prob. 51PSCh. 13 - Movie companies need to predict the gross receipts...Ch. 13 - Prob. 53PSCh. 13 - Prob. 54PSCh. 13 - Prob. 55PSCh. 13 - Based on a sample of n=20, the latest-squares...Ch. 13 - Prob. 57PSCh. 13 - In Problem 13.4 on page 493, you used the...Ch. 13 - In Problem 13.7 on page 494, you used the plate...Ch. 13 - In Problem 13.6 on page 494, a prospective MBA...Ch. 13 - Prob. 61PSCh. 13 - Prob. 62PSCh. 13 - In problem 13.10 on page 494, you used YouTube...Ch. 13 - Prob. 64PSCh. 13 - Prob. 65PSCh. 13 - When is the unexplained variation (i.e., error sum...Ch. 13 - Prob. 67PSCh. 13 - Prob. 68PSCh. 13 - Prob. 69PSCh. 13 - How do you evaluate the assumptions of regression...Ch. 13 - When and how do you use the Durbin-Watson...Ch. 13 - Prob. 72PSCh. 13 - Can you use movie critics’ opinions to forecast...Ch. 13 - Management of a soft-drink botting company has the...Ch. 13 - Measuring the height of a California redwood tree...Ch. 13 - You want to develop a model to predict the asking...Ch. 13 - You want to develop a model to predict the taxes...Ch. 13 - An analyst has the objective of predicting the...Ch. 13 - An accountant for a large department store has the...Ch. 13 - On January 28, 1986, the space shuttle Challenger...Ch. 13 - A baseball analyst would like to study various...Ch. 13 - Can you use the annual revenues generated by...Ch. 13 - In Problem 13.82 you used annual revenue to...Ch. 13 - During the fall harvest season in the United...Ch. 13 - Refer to the discussion of beta values and market...Ch. 13 - The file CEO 2016 includes the total compensation...Ch. 13 - In Problem 13.8, 13.20, 13.30, 13.46, 13.62,...
Knowledge Booster
Learn more about
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
- Olympic 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_forwardFind the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardIf your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?arrow_forward
- Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over the past year, and obtains the regressions results in the table shown below. A family purchases a 2000 square foot home and plans to make extensions totalling 500 square feet. The house currently has a pool, and a real estate agent has reported that the house is in excellent condition. However, the house does not have a view, and this will not change as a result of the extensions. According to the results in column (1), what is the expected DOLLAR increase in the price of the home due to the planned extensions?arrow_forwardSuppose a study wants to predict the market price of a certain species of turtle (Y) based on the following independent variables indicated in the table. Based from the table, what is the equation of the multiple linear regression? (Round off up to two decimal places. Market Price = 0.07 - 0.40*weight + 1.51*length + 1.41*width + 0.80*age Market Price = - 0.40*weight + 1.51*length + 1.41*width + 0.80*age Market Price = 0.07 + 0.40*weight + 1.51*length + 1.41*width + 0.80*age Market Price = 0.07 - 0.40 + weight + 1.51 + length + 1.41 + width + 0.80 + agearrow_forwardThe accountant at Bintong Chen Coal Distributors, Inc., in Newark, Delaware, notes that the demand for coal seems to be tied to an index of weather severity developed by the U.S. Weather Bureau. When weather was extremely cold in the U.S. over the past 5 years (and the index was thus high), coal sales were high. The accountant proposes that one good forecast of next year's coal demand could be made by developing a regression equation and then consulting the Farmer's Almanac to see how severe next year's winter would be. The data for coal sales are shown below: Coal Sales, y (in millions of tons) Weather Index, x 4 1 4 5 2 1 4 The least-squares regression equation that shows the best relationship between coal sales and weather index is (round your responses to one decimal place): ý = D+ x, where y = Coal Sales and x = Weather Index. The coefficient of correlation of the data, r, = (round your response to three decimal places). The standard error of the estimate = (round your response to…arrow_forward
- Suppose the athletic director at a university would like to develop a regression model to predict the point differential for games played by the men's basketball team. A point differential is the difference between the final points scored by two competing teams. A positive differential is a win, and a negative differential is a loss. For a random sample of games, the point differential was calculated, along with the number of assists, rebounds, turnovers, and personal fouls. Use the data in the accompanying table attached below to complete parts a through e below. Assume a = 0.05. a) Using technology, construct a regression model using all three independent variables. y = __ + (_)x1 + (_)x2 + (_)x3 + (_)x4 b) Test the significance of each independent variable using a= 0.10. c) interpret the p-value for each independent variable. d) Construxt a 90% confidence interval for the regression coefficients for each independent variable and interpret the meaning. e) Using the results from…arrow_forwardA researcher wants to investigate the influence of the average no. of nights spent per year by the tourists from Japan on the average amount spent by them. Table 3 shows the related data obtained from the Department of Statistics Malaysia website. Table 4 shows a portion of Microsoft Excel output for the regression analysis performed based on the data in Table 3. Table 3: Data on the nights spent by tourists from Japan and amount spent Year Average no. of nights spent Average amount spent (in RM billion) 2010 5.9 1.1 2011 6.1 1.1 2012 6.1 1.4 2013 6.3 1.5 2014 6.4 1.8 2015 6.1 1.6 2016 6.2 1.3 2017 6.3 1.2 2018 6.6 1.7 2019 6.9 2.3 Table 4: Regression analysis Coefficients Standard Error t Stat P-value Intercept B0 1.4555 -3.7583 0.0056 Average no. of nights spent B1 0.2312 4.7934 0.0014 a. Note that the value of B0 and B1 are missing from Table 4.…arrow_forwardSuppose Connie used regression to predict the height of a woman’s current boyfriend by using her own height as the explanatory variable. Height was measured in feet from a sample of 100 women undergraduates, and their boyfriends, at De La Salle Lipa. Now, suppose that the height of both the women and the men are converted to centimeters. The impact of this conversion on the slope is: the magnitude of the slope will change neither the sign nor magnitude of the slope will change the sign of the slope will change both the sign and magnitude of the slope will changearrow_forward
arrow_back_ios
arrow_forward_ios
Recommended textbooks for you
- Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillCalculus For The Life SciencesCalculusISBN:9780321964038Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.Publisher:Pearson Addison Wesley,Trigonometry (MindTap Course List)TrigonometryISBN:9781305652224Author:Charles P. McKeague, Mark D. TurnerPublisher:Cengage Learning
- Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage LearningCollege AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage LearningFunctions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Calculus For The Life Sciences
Calculus
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:Pearson Addison Wesley,
Trigonometry (MindTap Course List)
Trigonometry
ISBN:9781305652224
Author:Charles P. McKeague, Mark D. Turner
Publisher:Cengage Learning
Linear Algebra: A Modern Introduction
Algebra
ISBN:9781285463247
Author:David Poole
Publisher:Cengage Learning
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY