BASIC BUSINESS STATISTICS-STUD.SOLN.MAN
14th Edition
ISBN: 9780134685045
Author: BERENSON
Publisher: PEARSON
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Chapter 14, Problem 20PS
a.
To determine
Perform a residual analysis.
b.
To determine
Perform Durbin Watson test if appropriate.
c.
To determine
Determine whether the regression assumptions are valid for the data.
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13. Examine the following regression equation and answer the questions that follow:
Salary = 261,128 +91,569Goals + 16,346Assists - 585,560.Defenseman
(2.789) (9.641)
(3.301) (5.001)
R² = 0.65
Salary = NHL Player's Salary in $
Goals Number of goals scored by that player
Assists = Number of assists made by that player
Defenseman = Takes on a value of 1 if player is a defenseman. Otherwise, the value of this
variable is zero.
The numbers in brackets are t-statistics for the variables above them.
(a)
What salary will an offensive player make that scores no goals and has no assists?
Interpret the meaning of the R² in words.
(b)
(c)
What is the increase in salary from scoring one more goal (holding the number of assists
constant)?
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
1. An agent for a residential real estate company in a large city would like to be able to predict the monthly rental cost for apartments, based on the size of an apartment, as defined by square footage. The agent selects a sample of 25
apartments in a particular residential neighborhood and gathers the following data
a. determine the coefficient of determination, and interpret its meaning.
b. determine the standard error of the estimate.
c. How useful do you think this regression model is for predicting the monthly rent?
Chapter 14 Solutions
BASIC BUSINESS STATISTICS-STUD.SOLN.MAN
Ch. 14 - For this problem, use the following multiple...Ch. 14 - For this problem, use the following multiple...Ch. 14 - A nonprofit analyst seeks to determine which...Ch. 14 - Profitability remains a challenge for banks and...Ch. 14 - The production of wine is a multibillion-dollar...Ch. 14 - Human resource managers face the business problem...Ch. 14 - Prob. 7PSCh. 14 - Prob. 8PSCh. 14 - The following ANOVA summary table is for a...Ch. 14 - The following ANOVA summary table is for a...
Ch. 14 - A financial analyst engaged in business valuation...Ch. 14 - In Problem 14.3 on page 541, you predicted...Ch. 14 - In Problem 14.5 on page 542, you used the...Ch. 14 - In Problem 14.4 on page 541, you used efficiency...Ch. 14 - In Problem 14.7 on page 542, you used the weekly...Ch. 14 - Prob. 16PSCh. 14 - Prob. 17PSCh. 14 - Prob. 18PSCh. 14 - In Problem 14.5 on page 542, you used the...Ch. 14 - Prob. 20PSCh. 14 - Prob. 21PSCh. 14 - Prob. 22PSCh. 14 - Prob. 23PSCh. 14 - Prob. 24PSCh. 14 - In Problem 14.3 on page 541, you predicted...Ch. 14 - In Problem on page 541, you used efficiency ratio...Ch. 14 - Prob. 27PSCh. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - Prob. 29PSCh. 14 - Prob. 30PSCh. 14 - The following is the ANOVA summary table for a...Ch. 14 - The following is the ANOVA summary table for a...Ch. 14 - In Problem 14.5 on page 542, you used alcohol...Ch. 14 - In Problem 14.4 on page 541, you used efficiency...Ch. 14 - Prob. 35PSCh. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - Prob. 37PSCh. 14 - Suppose X1 is a numerical variable and X2 is a...Ch. 14 - The chair of the accounting department plans to...Ch. 14 - A real estate association in a suburban community...Ch. 14 - In Problem 14.5 on page 542, you developed a...Ch. 14 - In mining engineering, holes are often drilled...Ch. 14 - The owner of a moving company typically has his...Ch. 14 - Prob. 44PSCh. 14 - Zagat’s publishes restaurant rating for various...Ch. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - In Problem 14.5 on page 542, the percentage of...Ch. 14 - Prob. 48PSCh. 14 - The director of a training program for a large...Ch. 14 - Prob. 50PSCh. 14 - Prob. 51PSCh. 14 - Prob. 52PSCh. 14 - Prob. 53PSCh. 14 - Prob. 54PSCh. 14 - Prob. 55PSCh. 14 - Prob. 56PSCh. 14 - Prob. 57PSCh. 14 - An automotive insurance company wants to predict...Ch. 14 - A marketing manager wants to predict customer with...Ch. 14 - A local supermarket manager wants to use two...Ch. 14 - Prob. 61PSCh. 14 - Prob. 62PSCh. 14 - Prob. 63PSCh. 14 - Prob. 64PSCh. 14 - Prob. 65PSCh. 14 - Prob. 66PSCh. 14 - Prob. 67PSCh. 14 - Prob. 68PSCh. 14 - Prob. 69PSCh. 14 - Prob. 70PSCh. 14 - Prob. 71PSCh. 14 - The owner of a moving company typically has his...Ch. 14 - Professional basketball has truly become a sport...Ch. 14 - A sample of 61 house recently listed for sale in...Ch. 14 - Measuring the height of a California redwood tree...Ch. 14 - A sample of 61 houses recently listed for sale in...Ch. 14 - Prob. 77PSCh. 14 - Referring to Problem 14.77, Suppose that an...Ch. 14 - Prob. 79PSCh. 14 - Prob. 80PSCh. 14 - Prob. 81PSCh. 14 - Prob. 82PSCh. 14 - Prob. 83PS
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_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_forwardWhat does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forward
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- 10. Answer the following... What is linear regression used for? How do researchers set up and use the linear regression procedure to predict unknown Y scores? What is the symbol for a predicted Y score and what is it called?arrow_forwardWhat is C,D and E? And how do i calculate it??arrow_forward10. Terry's best friend, Heather, is the owner of Heather's Hondas. Like Terry, Heather sells used cars, and she too would like to try to predict the price of a used car based on the number of miles the car was driven by previous owners. When Heather creates a scatterplot, she notices a linear relationship between these two variables, and she obtains the following regression equation. Predicted price = 18855.05 – 0.101(miles) Heather also finds that r-squared is equal to 46.9%. This means the correlation (or r) between price and miles for Heather's sample of cars must be equal to what value?arrow_forward
- Connie Harris, who is in charge of office supplies at First Capital Mortgage Corp., would like to predict the quantity of paper used in the office photocopying machines per month. She believes that the number of loans originated in a month influence the volume of photocopying performed. She has compiled the following recent monthly data: Develop an estimated regression equation for this data set. Place output in cell G1 At .05 level of significance, is the equation significant? Why? Does the equation seem to have a good “fit”? Why? Forecast the amount of paper used in a month when 42 loan originations are expected. Loans Originated in Month Paper Used (000's) 45 22 25 13 50 24 60 25 40 21 25 16 35 18 40 25arrow_forwardA marketing manager conducted a study to determine the relationship between money spent on advertising (X) and company sales (Y). The study consisted of 8 companies and the data is given below and is in units of $1000s (ie. 2.4 = $2400.00) d. What is the resulting residual value when advertising expenditure is $2200.00 (X = 2.2), that is the difference between the actual observed value of y and the predicted value of y when using the fitted regression equation? e. What percentage of the variation in company sales is explained by the regression equation? In other words, what is the variability in Y that is due to advertising? Does a…arrow_forwardConsider the following passage: I ran a regression, with many variables to predict the result of another variable which was the murder rate. One can see that lots of things, can cause the murder rate to increase or decrease. I tried to account for all the important factors, and those factors are the SAT scores, unemployment rate, and international migration per 1,000. The SAT score is, average combined total score participants did on the SAT exam. The unemployment rate is, "a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force." (Wikipedia) International migration per 1,000 is, the number of people who come into a state from other countries per 1,000 people who live in the state. After I run the regression I will look at the t scores and p values and I should hopefully conclude that international migration does not cause crime. Which writing mistakes, if any, did…arrow_forward
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