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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Textbook Question
Chapter 3, Problem 71CP
Crime rate and urbanization For the data in Example 14 on crime in Florida, the regression line between y = crime rate (number of crimes per 1000 people) and x = percentage living in an urban environment is
- a. Using the slope, find the difference in predicted crime rates between counties that are 100% urban and counties that are 0% urban. Interpret.
- b. Interpret the
correlation of 0.67 between these variables. - c. Show the connection between the correlation and the slope, using the standard deviations of 28.3 for crime rate and 34.0 for percentage urban.
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Statistics: The Art and Science of Learning from Data (4th Edition)
Ch. 3.1 - Which is the response/explanatory variable? For...Ch. 3.1 - Sales and advertising Each month, the owner of...Ch. 3.1 - Does higher income make you happy? Every General...Ch. 3.1 - Diamonds The clarity and cut of a diamond are two...Ch. 3.1 - Alcohol and college students The Harvard School of...Ch. 3.1 - How to fight terrorism? A survey of 1000 adult...Ch. 3.1 - Heaven and hell Two questions on the General...Ch. 3.1 - Prob. 8PBCh. 3.1 - Gender gap in party ID In recent election years,...Ch. 3.1 - Use the GSS Go to the GSS website...
Ch. 3.2 - Used cars and direction of association For the 100...Ch. 3.2 - Broadband and GDP The Internet Use data file on...Ch. 3.2 - Prob. 13PBCh. 3.2 - Politics and newspaper reading For the FL Student...Ch. 3.2 - Prob. 15PBCh. 3.2 - Match the scatterplot with r Match the following...Ch. 3.2 - Prob. 17PBCh. 3.2 - Prob. 18PBCh. 3.2 - Prob. 19PBCh. 3.2 - Prob. 20PBCh. 3.2 - Prob. 21PBCh. 3.2 - Prob. 22PBCh. 3.2 - Prob. 23PBCh. 3.3 - Sketch plots of lines Identify the values of the...Ch. 3.3 - Prob. 25PBCh. 3.3 - Home selling prices The House Selling Prices FL...Ch. 3.3 - Prob. 27PBCh. 3.3 - Prob. 28PBCh. 3.3 - Prob. 29PBCh. 3.3 - Broadband subscribers and population The Internet...Ch. 3.3 - Prob. 31PBCh. 3.3 - Prob. 32PBCh. 3.3 - Regression between cereal sodium and sugar The...Ch. 3.3 - Prob. 34PBCh. 3.3 - Advertising and sales Each month, the owner of...Ch. 3.3 - Midtermfinal correlation For students who take...Ch. 3.3 - Predict final exam from midterm In an introductory...Ch. 3.3 - NL baseball Example 9 related y = team scoring...Ch. 3.3 - Study time and college GPA A graduate teaching...Ch. 3.3 - Oil and GDP An article in the September 16, 2006,...Ch. 3.3 - Mountain bikes revisited Is there a relationship...Ch. 3.3 - Mountain bike and suspension type Refer to the...Ch. 3.3 - Fuel Consumption Most cars are fuel efficient when...Ch. 3.4 - Extrapolating murder The SPSS figure shows the...Ch. 3.4 - Mens Olympic long jumps The Olympic winning mens...Ch. 3.4 - U.S. average annual temperatures Use the U.S....Ch. 3.4 - Murder and education Example 13 found the...Ch. 3.4 - Murder and poverty For Table 3.6, the regression...Ch. 3.4 - TV watching and the birth rate The figure shows...Ch. 3.4 - Looking for outliers Using software, analyze the...Ch. 3.4 - Regression between cereal sodium and sugar Let x =...Ch. 3.4 - Gestational period and life expectancy Does the...Ch. 3.4 - Antidrug campaigns An Associated Press story (June...Ch. 3.4 - Whats wrong with regression? Explain whats wrong...Ch. 3.4 - Education causes crime? The table shows a small...Ch. 3.4 - Death penalty and race The table shows results of...Ch. 3.4 - NAEP scores Eighth-grade math scores on the...Ch. 3.4 - Age a confounder? A study observes that the...Ch. 3 - Choose explanatory and response For the following...Ch. 3 - Graphing data For each case in the previous...Ch. 3 - Life after death for males and females In a recent...Ch. 3 - God and happiness Go to the GSS website...Ch. 3 - Degrees and income The mean annual salaries earned...Ch. 3 - Bacteria in ground turkey Consumer Reports...Ch. 3 - Women managers in the work force The following...Ch. 3 - RateMyProfessor.com The website RateMyProfessors....Ch. 3 - Women in government and economic life The OECD...Ch. 3 - African droughts and dust Is there a relationship...Ch. 3 - Crime rate and urbanization For the data in...Ch. 3 - Gestational period and life expectancy revisited...Ch. 3 - Height and paycheck The headline of an article in...Ch. 3 - Predicting college GPA An admissions officer...Ch. 3 - College GPA = high school GPA Refer to the...Ch. 3 - Whats a college degree worth? In 2002, a census...Ch. 3 - Care Weight and gas hogs: The table shows a short...Ch. 3 - Predicting Internet use from cell phone use We now...Ch. 3 - Income depends on education? For a study of...Ch. 3 - Fertility and GDP Refer to the Human Development...Ch. 3 - Women working and birth rate Using data from...Ch. 3 - Education and income The regression equation for a...Ch. 3 - Income in euros Refer to the previous exercise....Ch. 3 - Changing units for cereal data Refer to the Cereal...Ch. 3 - Murder and single-parent families For Table 3.6 on...Ch. 3 - Violent crime and college education For the U.S....Ch. 3 - Violent crime and high school education Repeat the...Ch. 3 - Crime and urbanization For the U.S. Statewide...Ch. 3 - High school graduation rates and health insurance...Ch. 3 - Womens Olympic high jumps Example 11 discussed how...Ch. 3 - Income and height A survey of adults revealed a...Ch. 3 - More TV watching goes with fewer babies? For...Ch. 3 - More sleep causes death? An Associated Press story...Ch. 3 - Ask Marilyn Marilyn vos Savant writes a column for...Ch. 3 - Time studying and GPA Is there a relationship...Ch. 3 - Warming in Newnan, Georgia Access the Newnan GA...Ch. 3 - Fluoride and AIDS An Associated Press story...Ch. 3 - Fish fights Alzheimers An AP story (July 22, 2003)...Ch. 3 - Dogs make you healthier A study published in the...Ch. 3 - Multiple choice: Correlate GPA and GRE In a study...Ch. 3 - Multiple choice: Properties of r Which of the...Ch. 3 - Multiple choice: Interpreting r One can interpret...Ch. 3 - Multiple choice: Correct statement about r Which...Ch. 3 - Multiple choice: Describing association between...Ch. 3 - Multiple choice: Slope and correlation The slope...Ch. 3 - Multiple choice: Interpretation of r2 An r2...Ch. 3 - True or false The variables y = annual income...Ch. 3 - Correlation doesnt depend on units Suppose you...Ch. 3 - When correlation = slope Consider the formula...Ch. 3 - Center of the data Consider the formula a=ybx for...Ch. 3 - Final exam regresses toward mean of midterm Let y...Ch. 3 - Activity: Guess the correlation The Guess the...
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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_forwardLife 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_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_forward
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