Intro Stats, Books a la Carte Edition (5th Edition)
5th Edition
ISBN: 9780134210285
Author: Richard D. De Veaux, Paul Velleman, David E. Bock
Publisher: PEARSON
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Chapter 20.5, Problem 5JC
To determine
Explain the way of changing the interpretation of the coefficient of height changed.
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Explain in brief the Utility of regression lines?
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After interviewing salespersons at Harley Davidson dealerships, a researcher has created a linear regression line to explain the relationship between a Harley Davidson motorcycle's age (x) and price (y). The regression has an = 87.7%. Write a sentence summarizing what says about this regression.
The age of the motorcycle explains 12.3% of the variation in price.
The age of the motorcycle explains 9.36% of the variation in price.
The age of the motorcycle explains 87.7% of the variation in price.
The price of the motorcycle explains 12.3% of the variation in age.
The price of the motorcycle explains 87.7% of the variation in age.
Chapter 20 Solutions
Intro Stats, Books a la Carte Edition (5th Edition)
Ch. 20.5 - Researchers in Food Science studied how big...Ch. 20.5 - Prob. 2JCCh. 20.5 - Prob. 3JCCh. 20.5 - Prob. 4JCCh. 20.5 - Prob. 5JCCh. 20.5 - Prob. 6JCCh. 20 - Graduate earnings Does attending college pay back...Ch. 20 - Shoot to score 2016 A college hockey coach...Ch. 20 - Prob. 3ECh. 20 - Shoot to score II Discuss the assumptions and...
Ch. 20 - Prob. 5ECh. 20 - Shoot to score, another one Using the regression...Ch. 20 - Prob. 7ECh. 20 - Shoot to score, hat trick Returning to the results...Ch. 20 - Prob. 9ECh. 20 - Shoot to score, number five What can the hockey...Ch. 20 - Prob. 11ECh. 20 - Prob. 12ECh. 20 - Prob. 13ECh. 20 - Prob. 14ECh. 20 - Prob. 15ECh. 20 - Shoot to score, double overtime Continuing from...Ch. 20 - Prob. 17ECh. 20 - Prob. 18ECh. 20 - Prob. 19ECh. 20 - Prob. 20ECh. 20 - Prob. 21ECh. 20 - Drug use 2013 The 2013 World Drug Report...Ch. 20 - Prob. 23ECh. 20 - Saratoga house prices How does the price of a...Ch. 20 - Prob. 25ECh. 20 - Prob. 26ECh. 20 - Prob. 27ECh. 20 - Prob. 28ECh. 20 - Prob. 29ECh. 20 - More cholesterol Look again at Exercise 28s...Ch. 20 - Prob. 31ECh. 20 - Cholesterol, finis Based on the regression output...Ch. 20 - Prob. 33ECh. 20 - Prob. 34ECh. 20 - Prob. 35ECh. 20 - Prob. 36ECh. 20 - Prob. 37ECh. 20 - Prob. 38ECh. 20 - Prob. 39ECh. 20 - Fuel economy A consumer organization has reported...Ch. 20 - Climate change 2016 Data collected from around the...Ch. 20 - Prob. 42ECh. 20 - Prob. 43ECh. 20 - Fuel economy, part III Consider again the data in...Ch. 20 - Climate change again Consider once again the CO2...Ch. 20 - Cereals A healthy cereal should be low in both...Ch. 20 - Brain size Does your IQ depend on the size of your...Ch. 20 - Prob. 48ECh. 20 - Prob. 49ECh. 20 - Prob. 50ECh. 20 - Ozone and population The Environmental Protection...Ch. 20 - Prob. 52ECh. 20 - Prob. 53ECh. 20 - More sales and profits Consider again the...Ch. 20 - Prob. 55ECh. 20 - Crawling Researchers at the University of Denver...Ch. 20 - Midterms The data set below shows midterm and...Ch. 20 - Prob. 58ECh. 20 - Prob. 59ECh. 20 - All the efficiency money can buy 2011 A sample of...Ch. 20 - Education and mortality The following software...Ch. 20 - Property assessments The following software output...Ch. 20 - Prob. 63ECh. 20 - Prob. 64E
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- Does Table 2 represent a linear function? If so, finda linear equation that models the data.arrow_forwardIf you travel 100 miles in two hours, then your average speed for the trip is Average speed=_________=________arrow_forwardWhat is regression analysis? Describe the process of performing regression analysis on a graphing utility.arrow_forward
- Life 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_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_forwardThe average height of people in Faroe island is 180cm. Suppose you run a regression with no independent variables. What would be the estimated form of your regression?arrow_forward
- Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS df 208.008457 314.295372 37 2 104.004228 8.49446952 MS 522.303829 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared Root MSE = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What is the predicted height for a child born to a mother…arrow_forwardResearchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight ), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 2 37 Interpret the intercept of this model. 104.004228 8.49446952 Coef. Std. Err. MS 39 13.3924059 .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .3591375 -.0797093 -15.32021 .9567683 .4804261 34.92886arrow_forwardResearchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 104.004228 2 37 8.49446952 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 Interpret the slope associated with mother's height. t P>|t| 4.46 0.000 с 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE = = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Intervall 9567683 .4804261 34.92886arrow_forward
- Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight ), and height of the father ( fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS df 208.008457 314.295372 37 522.303829 2 104.004228 8.49446952 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 Calculate the test statistic that is labeled "C" in the output. t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, Prob > F 37) = R-squared Adj R-squared = Root MSE 40 12.24 0.0001 = 0.3983 0.3657 2.9145 .3591375 -.0797093 -15.32021 = [95% Conf. Intervall .9567683 .4804261…arrow_forwardThe slope of a regression line tells you how much or little a change in your dependent variable impacts your independent variable. O TrueO Falsearrow_forwardWhy the regression line is a straight line rather than a curved line?arrow_forward
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