Introductory Statistics (2nd Edition)
2nd Edition
ISBN: 9780321978271
Author: Robert Gould, Colleen N. Ryan
Publisher: PEARSON
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Chapter 14, Problem 12SE
Homes Figure A shows a
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Chapter 14 Solutions
Introductory Statistics (2nd Edition)
Ch. 14 - Predicting Test Scores A professor tells his class...Ch. 14 - Used-Car Values A student wishes to buy a used...Ch. 14 - Height and Age (Example 1) A doctor says he can...Ch. 14 - Units and Semesters The registrar at a small...Ch. 14 - Buildings in Australia The table shows the height...Ch. 14 - Buildings in Singapore The table shows the number...Ch. 14 - Used BMWs (Example 2) Figure A shows a scatterplot...Ch. 14 - Pulse Rates Figure A shows a scatterplot with the...Ch. 14 - Semesters and Credits (Example 4) Figure A shows a...Ch. 14 - U.S. Population Figure A shows a scatterplot for...
Ch. 14 - Salaries Figure A shows a scatterplot of the...Ch. 14 - Homes Figure A shows a scatterplot of prices of...Ch. 14 - Wages of Twins Figure A shows a scatterplot of...Ch. 14 - Simulated Data Figure A shows a scatterplot of...Ch. 14 - Age and Weight (Example 5) DO older college...Ch. 14 - Age and Weight for Baseball Players Do older...Ch. 14 - Education of Parents (Example 7) Each of 29...Ch. 14 - Education of Parents Refer to exercise 14.17 and...Ch. 14 - Student and Parent Heights A random sample of 29...Ch. 14 - Trash The weight of trash (in pounds) produced by...Ch. 14 - Academic Performance index (Example 7) All...Ch. 14 - Father's and Mother's Education The output shows...Ch. 14 - Trash and Confidence Intervals The output provided...Ch. 14 - Movie Budgets In exercise 14.16 you examined the...Ch. 14 - Predicted GPA A student who has been accepted by...Ch. 14 - Used BMWs A used-car dealer is purchasing 50 used...Ch. 14 - Predicted Height (Example 9) A mother wants to...Ch. 14 - Predicted GPA A dean of students at a college...Ch. 14 - Loggers A logging company has the diameter of each...Ch. 14 - Height of Blind Date A female college student has...Ch. 14 - House Prices (Example 10) Figure A contains the...Ch. 14 - Math SAT Score and GPA Figure A shows information...Ch. 14 - Height and Weight A scatterplot of the heights and...Ch. 14 - Waist Size and Weight A scatterplot of the waist...Ch. 14 - GPA and SAT The figure shows 95#37; prediction...Ch. 14 - Shoes and Heights The scatterplot shows shoe size...Ch. 14 - Height and Weight A scatterplot of the heights and...Ch. 14 - Waist Size and Weight A scatterplot of the waist...Ch. 14 - Baseball Players Figure A shows a scatterplot with...Ch. 14 - Predicting Education Figure A shows a scatterplot...Ch. 14 - Life Expectancy and Gestation Periods for Animals...Ch. 14 - Math SAT Score and GPA Figure A shows information...
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_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_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_forward
- What is regression analysis? Describe the process of performing regression analysis on a graphing utility.arrow_forwardUsing your graphing calculator, make a scatter plot of the data from the table. Then graph your model from Question 2 along with the data. How well does your model fit the data? What could you do to try to improve your model?arrow_forwardNoise and Intelligibility Audiologists study the intelligibility of spoken sentences under different noise levels. Intelligibility, the MRT score, is measured as the percent of a spoken sentence that the listener can decipher at a cesl4ain noise level in decibels (dB). The table shows the results of one such test. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Find the correlation coefficient. Is a linear model appropriate? (d) Use the linear model in put (b) to estimate the intelligibility of a sentence at a 94-dB noise level.arrow_forward
- 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_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_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forward
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