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 15, Problem 37CP
To determine
Check whether nonparametric estimate of the slope is strongly affected by a regression outlier.
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A researcher is investigating possible explanations for deaths in traffic accidents. He examined data from 2000 for each of the 52 cities randomly selected in the US. The variables were death and income. Deaths: The number of deaths in traffic accidents per cityIncome: The median income per city
The researcher ran a simple linear regression model: Deaths = Bo+B1(Income). Results shown in photo below.
Question: Please help me better understand how to use results from photo to find value of R-squared of this simple linear regression model.
For a linear regression b1 is the estimated y-intercept, and b0is the estimated slope of the regression line.
true or false
For a linear regression b1 is the estimated y-intercept, and b0is the estimated slope of the regression line.
Chapter 15 Solutions
Statistics: The Art and Science of Learning from Data (4th Edition)
Ch. 15.1 - Prob. 1PBCh. 15.1 - Prob. 2PBCh. 15.1 - Prob. 3PBCh. 15.1 - Prob. 4PBCh. 15.1 - Prob. 5PBCh. 15.1 - Prob. 6PBCh. 15.1 - Prob. 7PBCh. 15.2 - How long do you tolerate being put on hold?...Ch. 15.2 - Prob. 9PBCh. 15.2 - Prob. 10PB
Ch. 15.2 - Cell phones and reaction times Example 13 in...Ch. 15.2 - Sign lest for GRR scores Consider Example 8, for...Ch. 15.2 - Prob. 13PBCh. 15.2 - More on blood pressure Refer to the previous...Ch. 15.2 - Prob. 15PBCh. 15.2 - Prob. 16PBCh. 15 - Car bumper damage An automobile company compares...Ch. 15 - Comparing more bumpers Refer to the previous...Ch. 15 - Telephone holding times In Exercise 15.8, the...Ch. 15 - Treating alcoholics The nonparametric statistics...Ch. 15 - Comparing tans Examples 1 and 2 compared two...Ch. 15 - Comparing therapies for anorexia The Anorexia data...Ch. 15 - Internet versus cell phones For the countries in...Ch. 15 - Prob. 24CPCh. 15 - GPAs The Georgia Student Survey data file has data...Ch. 15 - Prob. 26CPCh. 15 - Prob. 27CPCh. 15 - Student survey For the FL Student Survey data file...Ch. 15 - Prob. 29CPCh. 15 - Prob. 30CPCh. 15 - Complete the analogy The t test for comparing two...Ch. 15 - Prob. 32CPCh. 15 - True or false For a one-sided significance test...Ch. 15 - Multiple choice Nonparametric statistical methods...Ch. 15 - Prob. 35CPCh. 15 - Prob. 36CPCh. 15 - Prob. 37CP
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- XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. 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 the stock price to be in January 2012? January 2013?arrow_forwardDemand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00arrow_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_forward
- bThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.arrow_forwardRemainder Round all answers to two decimal places unless otherwise indicated. Domestic Auto Sales in the United States For 2005 through 2008, the following table shows the total U.S. sales, in millions, of domestic automobiles excluding light trucks. Date Domestic cars sold 2005 5.53 2006 5.48 2007 5.25 2008 4.54 a.Get the equation of the regression line rounding parameters to two decimal places, and explain in practical terms the meaning of the slope. In particular, comment on the meaning of the sign of the slope. b.Plot the data points and the regression line. c.In 2009, 3.62 million domestic cars were sold in the United States. How does the forecast obtained from the regression line compare with this figure?arrow_forwardA regression was run to determine whether there is arelationship between the diameter of a tree (x, in inches) and the tree’s age (y, in years). Theresults of the regression are given below. Use this topredict the age of a tree with diameter 10 inches. y=ax+ba=6.301b=1.044r=0.970arrow_forward
- What is interpolation when using a linear model?arrow_forwardmester 2021 English (en) - The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x1), the number of days in the month (x2), the average product purity (x3), and the tons of product produced (x4). A multiple linear regression analysis was applied to the experimental data using MINTAB and the following results were obtained: Regression Analysis: y versus x1, x2, x3, x4 Regression Equation y - -123 + 0.757 x1 + 7.52 x2+ 248 x3 - 0.481 x4 Coefficients Term Coef SE Coef T-Value P-Value VIF Constant -123 157 -0.78 0.459 x1 0.757 0.279 2.71 0.030 232 x2 7.52 4.01 1.87 0.103 216 x3 2.48 1.81 1.37 0.212 1,34 x4 -0.481 0.555 -0.87 0.415 1.01 Analysis of Variance Source DF Seg SS Seg MS F-Value P-Value Regression 4 5600.5 1400.1 10.08 0.005 Error 972.5 138.9 Total 11 6572.9 Then, an estimate of the error variance is equal to a. 157 b. 6572.9 C. 972.5 d. 138.9 e. 0.005 The electric power consumed each month by a chemical plant is…arrow_forwardFind the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. (b) x = 3.5 hours Hours spent studying, x Test score, y (a) x = 2 hours (c) x = 15 hours 1 2 4 40 45 51 49 62 67 (d) x = 1.5 hours Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)arrow_forward
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