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, Problem 76CP
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Match the given scatterplots to the description of its
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Select one:
a.
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Residuals versus correlation coefficients.
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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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- 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_forwardWhich of the following is not a plot of residuals typically used in multiple regression analysis? Select one: None of these Residuals versus correlation coefficients Residuals versus X1 Residuals versus time Residuals versus X2.arrow_forwardSir Francis Galton, in the late 1800s, was the first to introduce the statistical concepts of regression and correlation. He studied the relationships between pairs of variables such as the size of parents and the size of their offspring. Data similar to that which he studied are given below, with the variable x denoting the height (in centimeters) of a human father and the variable y denoting the height at maturity (in centimeters) of the father's oldest son. Height of father, x(in centimeters) Height of son, y(in centimeters) 171.6 180.5 193.1 188.9 186.1 187.3 161.7 172.9 173.6 174.6 180.0 188.1 156.0 174.5 200.6 190.5 191.2 196.1 191.2 189.3 186.2 175.3 172.5 171.4 182.2 177.7 174.8 178.9 161.7 167.2 The least-squares regression line for these data has a slope of approximately 0.53.Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. a. What is the value of the…arrow_forward
- On the second sheet is data which shows the rate of growth of a particular patch of bamboo vs daily high temperature.(a) Construct a scatterplot, including the equation of the line of best fit and value of R2.(b) What would the predicted growth rate be for a day with a temperature of 84◦?(c) Is there evidence, at α = 0.01, to support a claim that there is a linear relationship between temperature and growth rate? Please state clearly the null hypothesis, the alternative hypothesis, and what decision you make.arrow_forwardA group of students measure the length and width of a random sample of beans. They are interested in investigating the relationship between the length and width. Their summary statistics are displayed in the table below. All units, if applicable, are millimeters. Mean width: 7.586 Stdev width: 0.877 Mean height: 13.037 Stdev height: 1.697 Correlation coefficient: 0.7814 d) If the students are interested in using the height of the beans to predict the width, calculate the slope of this new regression equation. e) Write the equation of the best-fit line that can be used to predict bean widths. Use x to represent height and y to represent width.arrow_forwardOne set of 20 pairs of scores, X and Y values, produces a correlation of r = 0.70. If SSY = 150, calculate the standard error of the estimate for the regression linearrow_forward
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