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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Which command in R to get the coefficients of the regression line?
Chapter 8 Solutions
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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- Olympic 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_forwardThe following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardMore cereal Exercise 1 describes a regression model thatestimates a cereal’s potassium content from the amountof fiber it contains. In this context, what does it mean tosay that a cereal has a negative residual?arrow_forward
- Using the least-squares regression line, y=-25.5+1.5x, what is the residual for the data point at (28,19)?arrow_forwardDisk drives last time Here is a scatterplot of the residu-als from the regression of the hard drive prices on their sizes from Exercise 18.a) Are any assumptions or conditions violated? If so,which ones?b) What would you recommend about this regression?arrow_forwardd. Test the Overall significance of the regression hypothesis at the 5% level of significancearrow_forward
- Use Excel to find an estimated linear regression equation using X1 and X2 as the independent variables and Y as the dependent. Put your output on a fresh sheet. Then answer the following questions (excel chart in the picture) Write down the estimates regression equation What is the expected value of Y if X1 is 240 and X2 is 290? Show your calculation at a 5%level of significance, are the true coefficients of X1 and X2 different from zero? Justify briefly using numbers from your excel output. 4. Using Excel, determine a 97% confidence interval for the true coefficient of X1arrow_forwardWe want to estimate the effect of x on y using a simple linear regression. Assume that the MLR 1-6 hold and the true effect of x is zero. What is the probability that the t-statistic of the slope coefficient in the above regression is positive? a. 5% b. +/- 1.96 c. 95% d. 50%arrow_forward23) The values of the regression coefficients are found such the sum of the residuals is ___________.arrow_forward
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