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 8, Problem 10E
To determine
Explain whether removing all observations with large residuals is a good practice.
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Intro Stats, Books a la Carte Edition (5th Edition)
Ch. 8.3 - Each of these scatterplots shows an unusual point....Ch. 8.3 - Prob. 2JCCh. 8.3 - Prob. 3JCCh. 8.7 - Prob. 4JCCh. 8.7 - Prob. 5JCCh. 8.7 - Prob. 6JCCh. 8 - Credit card spending An analysis of spending by a...Ch. 8 - Prob. 2ECh. 8 - Prob. 3ECh. 8 - Prob. 4E
Ch. 8 - Prob. 5ECh. 8 - Prob. 6ECh. 8 - Prob. 7ECh. 8 - Prob. 8ECh. 8 - Prob. 9ECh. 8 - Prob. 10ECh. 8 - Skinned knees There is a strong correlation...Ch. 8 - Prob. 12ECh. 8 - Prob. 13ECh. 8 - Average GPA An athletic director proudly states...Ch. 8 - Prob. 15ECh. 8 - Prob. 16ECh. 8 - BK protein Recall the data about the Burger King...Ch. 8 - Prob. 18ECh. 8 - Prob. 19ECh. 8 - Prob. 20ECh. 8 - Prob. 21ECh. 8 - Prob. 22ECh. 8 - Prob. 23ECh. 8 - Prob. 24ECh. 8 - Good model? In justifying his choice of a model, a...Ch. 8 - Prob. 26ECh. 8 - Movie dramas Heres a scatterplot of the production...Ch. 8 - Prob. 28ECh. 8 - Oakland passengers 2016 The scatterplot below...Ch. 8 - Prob. 30ECh. 8 - Unusual points Each of these four scatterplots...Ch. 8 - More unusual points Each of the following...Ch. 8 - Prob. 33ECh. 8 - Prob. 34ECh. 8 - Prob. 35ECh. 8 - Whats the effect? A researcher studying violent...Ch. 8 - Reading To measure progress in reading ability,...Ch. 8 - Prob. 38ECh. 8 - Heating After keeping track of his heating...Ch. 8 - Speed How does the speed at which you drive affect...Ch. 8 - Prob. 41ECh. 8 - Prob. 42ECh. 8 - TBill rates 2016 revisited In Exercise 41, you...Ch. 8 - Prob. 44ECh. 8 - Prob. 45ECh. 8 - Prob. 46ECh. 8 - Elephants and hippos We removed humans from the...Ch. 8 - Prob. 48ECh. 8 - Prob. 49ECh. 8 - Prob. 50ECh. 8 - Prob. 51ECh. 8 - Prob. 52ECh. 8 - Inflation 2016 The Consumer Price Index (CPI)...Ch. 8 - Prob. 54ECh. 8 - Prob. 55ECh. 8 - Prob. 56ECh. 8 - Prob. 57ECh. 8 - Prob. 58ECh. 8 - Prob. 59ECh. 8 - Prob. 60ECh. 8 - Prob. 61ECh. 8 - Prob. 62ECh. 8 - Prob. 63ECh. 8 - Boyle Scientist Robert Boyle examined the...Ch. 8 - Brakes The following table shows stopping...Ch. 8 - Pendulum A student experimenting with a pendulum...Ch. 8 - Planets Here is a table of the 9 sun-orbiting...Ch. 8 - Is Pluto a planet? Lets look again at the pattern...Ch. 8 - Planets and asteroids The asteroid belt between...Ch. 8 - Prob. 71ECh. 8 - Prob. 72ECh. 8 - Logs (not logarithms) The value of a log is based...Ch. 8 - Prob. 74ECh. 8 - Life expectancy history The table gives the Life...Ch. 8 - Prob. 76ECh. 8 - Prob. 77ECh. 8 - Prob. 78ECh. 8 - Prob. 79ECh. 8 - Prob. 80E
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- If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?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_forwardFind the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forward
- For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyarrow_forwardFor the following exercises, consider this scenario: The profit of a company decreased steadily overa ten-year spam.The following ordered pairs shows dollars and the number of units sold in hundreds and the profit in thousands ofover the ten-year span, (number of units sold, profit) for specific recorded years: (46,600),(48,550),(50,505),(52,540),(54,495). Use linear regression to determine a function Pwhere the profit in thousands of dollars depends onthe number of units sold in hundreds.arrow_forwardFor the following table of data. x 1 2 3 4 5 6 7 8 9 10 y 0 0.5 1 2 2.5 3 3 4 4.5 5 a. draw a scatterplot. b. calculate the correlation coefficient. c. calculate the least squares line and graph it on the scatterplot. d. predict the y value when x is 11.arrow_forward
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