Pearson eText for Basic Business Statistics -- Instant Access (Pearson+)
14th Edition
ISBN: 9780137400119
Author: MARK BERENSON, David Levine
Publisher: PEARSON+
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Chapter 14, Problem 53PS
a.
To determine
Interpret the meaning of a logistic regression coefficient.
b.
To determine
Find the estimated odds ratio and interpret its meaning.
c.
To determine
Find estimated probability of an
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xx=02
A regression of average monthly expenditure (AME, measured in euros) on average monthly income (AMI, measured in euros) using a random sample of college-educated full-time workers earnings €100 to €1.5 million yields the following:
AME = 710.7 + 8.8 × AMI, R2 = 0.030, SER = 540.30
d. What does the regression predict will be the expenditure of a person with an income of €100? With an income of €200?
e. Will the regression give reliable predictions for a person with an income of €2 million? Why or why not? (
f. Given what you know about the distribution of earnings, do you think it is plausible that the distribution of errors in the regression is normal? (Hint: Do you think that the distribution is symmetric or skewed? What is the smallest value of earnings, and is it consistent with a normal distribution?).
Using your dataset, run a regression of Y=GPA and X=# Friends.(Ido not need your actual data, just the regression results)a) State what this regression is attempting to analyze. “By running this regression, we areattempting to show.....”b) Write out the regression equation and describe what it shows (if Friends increase by 1, then. . . ).c) Find your hypothesized GPA when the # friends equals 17.d) Is the slope of # of Friends significantly different from zero?Include Ho, Ha, decision rule, t statistic from table, tc, decision, and conclusion.e) Is the r-squared of # of Friends significantly different from zero?Include Ho, Ha, decision rule, F statistic from table, Fc, decision, and conclusion.
Chapter 14 Solutions
Pearson eText for Basic Business Statistics -- Instant Access (Pearson+)
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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- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardCable TV The following table shows the number C. in millions, of basic subscribers to cable TV in the indicated year These data are from the Statistical Abstract of the United States. Year 1975 1980 1985 1990 1995 2000 C 9.8 17.5 35.4 50.5 60.6 60.6 a. Use regression to find a logistic model for these data. b. By what annual percentage would you expect the number of cable subscribers to grow in the absence of limiting factors? c. The estimated number of subscribers in 2005 was 65.3million. What light does this shed on the model you found in part a?arrow_forwardFind the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forward
- Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardFor the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyarrow_forwardA regression analysis was performed to predict weight (y, in kg) using height (x, in cm) among 150 children. The coefficient of determination was . Which of the following is a valid interpretation? a. For each 1-cm increase in height, weight tends to increase by about 0.32 kg b. There is no association between weight and height c. Height accounts for about 32% of the total variability in weight d. The correlation between weight and height is about 0.32arrow_forward
- The use of multiple logistic regression is warranted when there are two or more independent quantitative or nominal variables and one dichotomous dependent variable. a. True b. Falsearrow_forwardA regression was run to determine if there is a relationship between the happiness inde expectancy in years of a given country (x). The results of the regression were: ŷ=a+bx a=-1.042 b=0.186arrow_forward1.Write the logistic regression equation to model the odds of distress as a function of temperature. Call: glm(formula = as.factor(distress) ~ temp, family = "binomial", data = ONE) Deviance Residuals: Min 1Q Median 3Q Max -1.0611 -0.7613 -0.3783 0.4524 2.2175 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 15.0429 7.3786 2.039 0.0415 * temp -0.2322 0.1082 -2.145 0.0320 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 28.267 on 22 degrees of freedom Residual deviance: 20.315 on 21 degrees of freedom AIC: 24.315 Number of Fisher Scoring iterations: 5 Logit = log (odds) = log{p/(1-p)}= α+β1X1+ β2X2 +…+βiXiarrow_forward
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