EP STATISTICS:ART+SCI...-MYLABSTATISTIC
4th Edition
ISBN: 9780135989029
Author: Agresti
Publisher: PEARSON CO
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Chapter 14.2, Problem 17PB
REM regression Refer to the previous exercise.
- a. Set up indicator variables for a regression model so that an F test for the regression parameters is equivalent to the ANOVA test comparing the three
means . - b. Express the null hypothesis both in terms of population means and in terms of regression parameters for the model in part a.
- c. The prediction equation from fitting the multiple regression model equals
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Chapter 14 Solutions
EP STATISTICS:ART+SCI...-MYLABSTATISTIC
Ch. 14.1 - Hotel satisfaction The CEO of a company that owns...Ch. 14.1 - Prob. 2PBCh. 14.1 - Whats the best way to learn French? The following...Ch. 14.1 - Prob. 4PBCh. 14.1 - Prob. 5PBCh. 14.1 - ANOVA and box plots For two studies, each...Ch. 14.1 - Prob. 7PBCh. 14.1 - Smoking and personality A study about smoking and...Ch. 14.1 - Prob. 9PBCh. 14.1 - Prob. 10PB
Ch. 14.1 - Prob. 11PBCh. 14.2 - House prices and age For the House Selling Prices...Ch. 14.2 - Time on Facebook Do freshmen spent significantly...Ch. 14.2 - Prob. 14PBCh. 14.2 - Tukey holding time comparisons Refer to the...Ch. 14.2 - Prob. 16PBCh. 14.2 - REM regression Refer to the previous exercise. a....Ch. 14.2 - Prob. 18PBCh. 14.2 - Regression for outsourcing Refer to the previous...Ch. 14.2 - Advertising effect oil sales Each of 100...Ch. 14.3 - Reducing cholesterol An experiment randomly...Ch. 14.3 - Prob. 24PBCh. 14.3 - Political ideology in 2014 The GSS measures...Ch. 14.3 - Prob. 26PBCh. 14.3 - Corn and manure In Example 10, the coefficient of...Ch. 14.3 - Prob. 28PBCh. 14.3 - Regression for telephone holding times Refer to...Ch. 14.3 - Prob. 30PBCh. 14.3 - Income by gender and degree In 2012, the...Ch. 14.3 - Prob. 32PBCh. 14.3 - Attractiveness and getting dates The results in...Ch. 14.3 - Prob. 34PBCh. 14.3 - Regression of weight gain on diet Refer to the...Ch. 14 - Good friends and marital status Is the number of...Ch. 14 - Prob. 37CPCh. 14 - Singles watch more TV The 2014 General Social...Ch. 14 - Prob. 39CPCh. 14 - Prob. 40CPCh. 14 - Prob. 41CPCh. 14 - Prob. 42CPCh. 14 - Prob. 43CPCh. 14 - Comparing therapies for anorexia The Anorexia data...Ch. 14 - Prob. 45CPCh. 14 - Prob. 46CPCh. 14 - Prob. 47CPCh. 14 - Prob. 48CPCh. 14 - Prob. 49CPCh. 14 - Prob. 50CPCh. 14 - Prob. 51CPCh. 14 - TV watching by gender and race When we use the...Ch. 14 - Prob. 53CPCh. 14 - Prob. 54CPCh. 14 - Prob. 55CPCh. 14 - Prob. 56CPCh. 14 - Prob. 57CPCh. 14 - Prob. 59CPCh. 14 - Prob. 60CPCh. 14 - Prob. 61CPCh. 14 - Prob. 62CPCh. 14 - Prob. 63CPCh. 14 - Prob. 64CPCh. 14 - Prob. 65CPCh. 14 - Prob. 66CPCh. 14 - Prob. 67CPCh. 14 - Prob. 68CPCh. 14 - Prob. 69CPCh. 14 - Prob. 70CPCh. 14 - Prob. 71CP
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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_forwardFind the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardUse appropriate statistical tables when necessary. What is the dependent and independent variables? Fully write out the regression equation. Fill in the missing values * and **. Test whether ᵟ is significant and give reasons for your answer.arrow_forward
- An engineer at a company wants to model the relationship between the yield (y) and three variables: pressure (x1), volume (x2) and temperature (x3). Data is collected and the output of the statistical analysis is displayed table below. i. From appropriate statistical tests, determine the relationship between yield and the three variables, Use a 5% significance level where required.arrow_forwardLet’s assume a particular sample of Math classes contains several student GPAs from a minimum of 3.3 and a maximum of 4.0. The researcher would like to use a regression line to make estimations for future students who take this class and eventually graduate. Another student in a History class whose GPA is 3.1 would also like to use this regression line. (a) Can this regression line be used for the History student? Explain.arrow_forwardA business statistics professor would like to develop a regression model to predict the final exam scores for students based on their current GPAs, the number of hours they studied for the exam, the number of times they were absent during the semester, and their genders. The data for these variables are given in the accompanying table at the bottom of this page. a) Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student ( this assignment is arbitrary) complete the regression equation for the model below, where y= Score, x1= GPA, x2= Hours, x3= Absenses, and x4= Gen. y= (__) + (__)x1 + (__)x2 + (__)x3 + (__)x4 b) Test the significance of the overall regression model using a= 0.10. c) interpret the meaning of the regression coefficient for the dummy variable. d) using the p-values, identify which independent variables are significant with a= 0.10. e) construct a regression…arrow_forward
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