Statistics: The Art and Science of Learning from Data (4th Edition)
4th Edition
ISBN: 9780321997838
Author: Alan Agresti, Christine A. Franklin, Bernhard Klingenberg
Publisher: PEARSON
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Chapter 12.5, Problem 57PB
a.
To determine
Show that the predicted population sizes are 81.14 million in 1900 and 323.3 million in 2010.
b.
To determine
Explain how to interpret the value 1.1339 in the prediction equation.
c.
To determine
Explain what
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Chapter 12 Solutions
Statistics: The Art and Science of Learning from Data (4th Edition)
Ch. 12.1 - Car mileage and weight The Car Weight and Mileage...Ch. 12.1 - Prob. 2PBCh. 12.1 - Predicting maximum bench strength in males For the...Ch. 12.1 - Prob. 4PBCh. 12.1 - Mu, not y For a population regression equation,...Ch. 12.1 - Prob. 6PBCh. 12.1 - Study time and college GPA Exercise 3.39 in...Ch. 12.1 - Prob. 8PBCh. 12.1 - Cell phone specs Refer to the cell phone data set...Ch. 12.1 - Prob. 10PB
Ch. 12.2 - t-score? A regression analysis is conducted with...Ch. 12.2 - Prob. 12PBCh. 12.2 - Confidence interval for slope Refer to the...Ch. 12.2 - Prob. 14PBCh. 12.2 - Strength through leg press The high school female...Ch. 12.2 - Prob. 16PBCh. 12.2 - More girls are good? Repeat the previous exercise...Ch. 12.2 - CI and two-sided tests correspond Refer to the...Ch. 12.2 - Advertising and sales Each month, the owner of Caf...Ch. 12.2 - Prob. 20PBCh. 12.2 - GPA and skipping classrevisited Refer to the...Ch. 12.2 - Prob. 22PBCh. 12.3 - Dollars and thousands of dollars If a slope is...Ch. 12.3 - Prob. 24PBCh. 12.3 - Sketch scatterplot Sketch a scatterplot,...Ch. 12.3 - Prob. 26PBCh. 12.3 - Body fat For the Male Athlete Strength data file...Ch. 12.3 - Prob. 28PBCh. 12.3 - SAT regression toward mean Refer to the previous...Ch. 12.3 - Prob. 30PBCh. 12.3 - GPA and study time Refer to the association you...Ch. 12.3 - Prob. 32PBCh. 12.3 - Does tutoring help? For a class of 100 students,...Ch. 12.3 - Prob. 34PBCh. 12.3 - Golf regression In the first round of a golf...Ch. 12.3 - Prob. 36PBCh. 12.3 - Food and drink sales The owner of Berthas...Ch. 12.3 - Prob. 38PBCh. 12.3 - Violent crime and single-parent families Use...Ch. 12.4 - Poor predicted strengths The MINITAB output shows...Ch. 12.4 - Prob. 42PBCh. 12.4 - Bench press residuals The figure is a histogram of...Ch. 12.4 - Predicting house prices The House Selling Prices...Ch. 12.4 - Predicting clothes purchases For a random sample...Ch. 12.4 - Prob. 46PBCh. 12.4 - ANOVA table for leg press Exercise 12.15 referred...Ch. 12.4 - Prob. 48PBCh. 12.4 - Variability and F Refer to the previous two...Ch. 12.4 - Understanding an ANOVA table For a random sample...Ch. 12.4 - Predicting cell phone weight Refer to the cell...Ch. 12.4 - Cell phone ANOVA Report the ANOVA table for the...Ch. 12.5 - Savings grow exponentially You invest 100 in a...Ch. 12.5 - Prob. 55PBCh. 12.5 - Prob. 56PBCh. 12.5 - Prob. 57PBCh. 12.5 - Prob. 58PBCh. 12.5 - Prob. 59PBCh. 12.5 - Prob. 60PBCh. 12.5 - Prob. 61PBCh. 12 - Prob. 62CPCh. 12 - Prob. 63CPCh. 12 - Prob. 64CPCh. 12 - Prob. 65CPCh. 12 - Prob. 66CPCh. 12 - Prob. 67CPCh. 12 - Prob. 68CPCh. 12 - Prob. 69CPCh. 12 - Prob. 70CPCh. 12 - Prob. 71CPCh. 12 - Prob. 72CPCh. 12 - Prob. 73CPCh. 12 - Prob. 74CPCh. 12 - World population growth The table shows the world...Ch. 12 - Prob. 76CPCh. 12 - Prob. 77CPCh. 12 - Prob. 78CPCh. 12 - Prob. 79CPCh. 12 - Prob. 81CPCh. 12 - Prob. 82CPCh. 12 - Prob. 83CPCh. 12 - Prob. 84CPCh. 12 - Prob. 85CPCh. 12 - Prob. 86CPCh. 12 - Prob. 87CPCh. 12 - Prob. 88CPCh. 12 - Prob. 89CPCh. 12 - Assumptions What assumptions are needed to use the...Ch. 12 - Assumptions fail? Refer to the previous exercise....Ch. 12 - Lots of standard deviations Explain carefully the...Ch. 12 - Decrease in home values A Freddie Mac quarterly...Ch. 12 - Population growth Exercise 12.57 about U.S....Ch. 12 - Multiple choice: Interpret r One can interpret r =...Ch. 12 - Multiple choice: Correlation invalid The...Ch. 12 - Multiple choice: Slope and correlation The slope...Ch. 12 - Multiple choice: Regress x on y The regression of...Ch. 12 - Multiple choice: Income and height University of...Ch. 12 - True or false The variables y = annual income...Ch. 12 - Prob. 101CPCh. 12 - Why is there regression toward the mean? Refer to...Ch. 12 - Prob. 103CPCh. 12 - Prob. 104CPCh. 12 - Prob. 105CPCh. 12 - Prob. 106CP
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- What is regression analysis? Describe the process of performing regression analysis on a graphing utility.arrow_forwardWhat does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardTable 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?arrow_forward
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- 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 mean hourly cost when the cell phone described above is used for 240 minutes.arrow_forward**Based on the regression results, answer the following questions** Data are collected on the income (measured in $1000’s of $’s), house value (measured in $1000’s of $’s), years in a home, age, sex (=1 for male, =0 for female), and the amount outstanding on a mortgage (measured in $1000’s of $’s). The dependent variable is income. Based on the regression results, answer the following questions b) What is the estimated regression equation? c) How much of the variation in income is explained by the regressors? d) What is the standard error of the error term in the regression equation?arrow_forward
- **Based on the regression results, answer the following questions** Data are collected on the income (measured in $1000’s of $’s), house value (measured in $1000’s of $’s), years in a home, age, sex (=1 for male, =0 for female), and the amount outstanding on a mortgage (measured in $1000’s of $’s). The dependent variable is income. Based on the regression results, answer the following questions e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the predicted value of income for a person that has been in a house for 5 years, is 38 years old, is a male, has a house valued at $250,000, and has $100,000 left on their mortgage? (g) What is the effect on the income of a person being a male versus a female?arrow_forwardDefine the different ways to use linear regression?arrow_forwardScenario: A medical researcher wishes to see whether there is a relationship between a person's age, cholesterol level, and systolic blood pressure. Eight people are randomly selected. The data is listed in the table. First, find the multiple regression equation. Next, determine the coefficient of determination. Then, use the regression equation to predict a person's blood pressure reading if the person selected is 50 years old with a cholesterol reading of 220. Age Cholesterol level Blood pressure Person 1 38 220 116 Person 2 41 225 120 Person 3 45 200 123 Person 4 48 190 131 Person 5 51 250 142 Person 6 53 215 145 Person 7 57 200 148 Person 8 61 170 150 Discussion Prompts Respond to the following prompts in your initial post: 1. Identify the explanatory variables and response variable for the data. 2. What is the multiple regression equation for the data? 3. What is the coefficient of determination? 4. If a person 50 years old with a cholesterol of 220 is selected, what is that…arrow_forward
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