Statistics: The Art and Science of Learning from Data (4th Edition)
4th Edition
ISBN: 9780321997838
Author: Alan Agresti, Christine A. Franklin, Bernhard Klingenberg
Publisher: PEARSON
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Chapter 12, Problem 103CP
To determine
Explain the reason why approximately the estimated variance of the conditional distribution of y for a given x is 30% smaller than the estimated variance of the marginal distribution of y.
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Chapter 12 Solutions
Statistics: The Art and Science of Learning from Data (4th Edition)
Ch. 12.1 - Car mileage and weight The Car Weight and Mileage...Ch. 12.1 - Prob. 2PBCh. 12.1 - Predicting maximum bench strength in males For the...Ch. 12.1 - Prob. 4PBCh. 12.1 - Mu, not y For a population regression equation,...Ch. 12.1 - Prob. 6PBCh. 12.1 - Study time and college GPA Exercise 3.39 in...Ch. 12.1 - Prob. 8PBCh. 12.1 - Cell phone specs Refer to the cell phone data set...Ch. 12.1 - Prob. 10PB
Ch. 12.2 - t-score? A regression analysis is conducted with...Ch. 12.2 - Prob. 12PBCh. 12.2 - Confidence interval for slope Refer to the...Ch. 12.2 - Prob. 14PBCh. 12.2 - Strength through leg press The high school female...Ch. 12.2 - Prob. 16PBCh. 12.2 - More girls are good? Repeat the previous exercise...Ch. 12.2 - CI and two-sided tests correspond Refer to the...Ch. 12.2 - Advertising and sales Each month, the owner of Caf...Ch. 12.2 - Prob. 20PBCh. 12.2 - GPA and skipping classrevisited Refer to the...Ch. 12.2 - Prob. 22PBCh. 12.3 - Dollars and thousands of dollars If a slope is...Ch. 12.3 - Prob. 24PBCh. 12.3 - Sketch scatterplot Sketch a scatterplot,...Ch. 12.3 - Prob. 26PBCh. 12.3 - Body fat For the Male Athlete Strength data file...Ch. 12.3 - Prob. 28PBCh. 12.3 - SAT regression toward mean Refer to the previous...Ch. 12.3 - Prob. 30PBCh. 12.3 - GPA and study time Refer to the association you...Ch. 12.3 - Prob. 32PBCh. 12.3 - Does tutoring help? For a class of 100 students,...Ch. 12.3 - Prob. 34PBCh. 12.3 - Golf regression In the first round of a golf...Ch. 12.3 - Prob. 36PBCh. 12.3 - Food and drink sales The owner of Berthas...Ch. 12.3 - Prob. 38PBCh. 12.3 - Violent crime and single-parent families Use...Ch. 12.4 - Poor predicted strengths The MINITAB output shows...Ch. 12.4 - Prob. 42PBCh. 12.4 - Bench press residuals The figure is a histogram of...Ch. 12.4 - Predicting house prices The House Selling Prices...Ch. 12.4 - Predicting clothes purchases For a random sample...Ch. 12.4 - Prob. 46PBCh. 12.4 - ANOVA table for leg press Exercise 12.15 referred...Ch. 12.4 - Prob. 48PBCh. 12.4 - Variability and F Refer to the previous two...Ch. 12.4 - Understanding an ANOVA table For a random sample...Ch. 12.4 - Predicting cell phone weight Refer to the cell...Ch. 12.4 - Cell phone ANOVA Report the ANOVA table for the...Ch. 12.5 - Savings grow exponentially You invest 100 in a...Ch. 12.5 - Prob. 55PBCh. 12.5 - Prob. 56PBCh. 12.5 - Prob. 57PBCh. 12.5 - Prob. 58PBCh. 12.5 - Prob. 59PBCh. 12.5 - Prob. 60PBCh. 12.5 - Prob. 61PBCh. 12 - Prob. 62CPCh. 12 - Prob. 63CPCh. 12 - Prob. 64CPCh. 12 - Prob. 65CPCh. 12 - Prob. 66CPCh. 12 - Prob. 67CPCh. 12 - Prob. 68CPCh. 12 - Prob. 69CPCh. 12 - Prob. 70CPCh. 12 - Prob. 71CPCh. 12 - Prob. 72CPCh. 12 - Prob. 73CPCh. 12 - Prob. 74CPCh. 12 - World population growth The table shows the world...Ch. 12 - Prob. 76CPCh. 12 - Prob. 77CPCh. 12 - Prob. 78CPCh. 12 - Prob. 79CPCh. 12 - Prob. 81CPCh. 12 - Prob. 82CPCh. 12 - Prob. 83CPCh. 12 - Prob. 84CPCh. 12 - Prob. 85CPCh. 12 - Prob. 86CPCh. 12 - Prob. 87CPCh. 12 - Prob. 88CPCh. 12 - Prob. 89CPCh. 12 - Assumptions What assumptions are needed to use the...Ch. 12 - Assumptions fail? Refer to the previous exercise....Ch. 12 - Lots of standard deviations Explain carefully the...Ch. 12 - Decrease in home values A Freddie Mac quarterly...Ch. 12 - Population growth Exercise 12.57 about U.S....Ch. 12 - Multiple choice: Interpret r One can interpret r =...Ch. 12 - Multiple choice: Correlation invalid The...Ch. 12 - Multiple choice: Slope and correlation The slope...Ch. 12 - Multiple choice: Regress x on y The regression of...Ch. 12 - Multiple choice: Income and height University of...Ch. 12 - True or false The variables y = annual income...Ch. 12 - Prob. 101CPCh. 12 - Why is there regression toward the mean? Refer to...Ch. 12 - Prob. 103CPCh. 12 - Prob. 104CPCh. 12 - Prob. 105CPCh. 12 - Prob. 106CP
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- To estimate the value of a dependent variable based on the values of one or more independent variables, the process used is called: Correlation Regression Slope Intercept Residualarrow_forwardA linear relationship exists between two variables x and y. The correlation coefficient was calculated for the sample data and is equal to -0.93. Using the estimated regression equation, a straight line that will best fit the data points can be drawn through the points on the scattergram.The line slopes downward from left to right and the points are scattered close to the line. True or falsearrow_forwardA linear relationship exists between two variables x and y. The correlation coefficient was calculated for the sample data and is equal to -0.93. Using the estimated regression equation, a straight line that will best fit the data points can be drawn through the points on the scattergram. The line slopes downward from left to right and the points are not scattered close to the line. True or falsearrow_forward
- Figure shows three residual plots and a normal probability plot of residuals. For each part, decide whether the graph suggests violation of one or more of the assumptions for regression inferences. Explain your answers.arrow_forwardThe residual is the difference between the observed value of the independent variable and the predicted value of the independent variable. TRUE FALSEarrow_forward5. TRUE or FALSE: The residual value is the difference between the observed y- value and the predictedy- value, yˆ .arrow_forward
- A multiple regression model has the form y^=b0+b1x1+b2x2 The coefficient b1 is interpreted as the:A. change in y per unit change in x1, holding x2 constantB. change in the average value of y per unit change in x1, holding x2 constantC. change in y per unit change in x1, when x1 and x2 values are correlatedD. change in y per unit change in x1 If multicollinearity exists among the independent variables included in a multiple regression model, the:A. multiple coefficient of determination will assume a value close to zeroB. standard errors of the regression coefficients for the correlated independent variables will increaseC. regression coefficients will be difficult to interpretD. regression coefficients will be difficult to interpret and the standard errors of the regression coefficients for the correlated independent variables will increase please explain which answer is correct and whyarrow_forwardThe individual residual scores from a sample of participants regarding the difference between the predicted Y values from a regression equation and the actual Y from the data are provided here. Y - Ŷ = 3,8,1,2,2. What is the value for the standard error of estimate?arrow_forward"What does R-squared (R^2) represent in the context of linear regression? Options: A. The slope of the regression line B. The correlation between the independent and dependent variables C. The proportion of the variance in the dependent variable that is predictable from the independent variable D. The intercept of the regression line"arrow_forward
- A pumpkin farmer wants to create a linear regression model to predict the circumference of a pumpkin (Y-variable) from its weight (X-variable). He samples 40 pumpkins from his pumpkin patch and the mean weight is 14 lbs with a standard deviation of 1 lb. The mean circumference is 50 inches with a standard deviation of 10 inches. The correlation between pumpkin weight and circumference is r = 0.50. What is the slope of the linear regression model predicting circumference from weight? 7 1 5 3arrow_forwardWhich of the following is FALSE? * The regression model assumes the errors (residuals) are normally distributed. Data point below the regression line, the residual is negative. The errors (residuals) in a regression model are assumed to have a zero mean. The errors (residuals) in a regression model are assumed to have increasing mean. In regression analysis, the regression line Minimize the sum of distances between the actual value x and the predicted x values. Minimize the perpendicular distance between the regression line and each data point. Minimize the sum of the squared residuals between the actual x and the predicted x values. Minimize the sum of the squared residuals between the actual y and the predicted y values. The smaller the distance between observed data points and the regression line, the smaller the sum of squares regression (SSR). TRUE FALSEarrow_forwardA trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x, = distance traveled (miles) and x, = the number of deliveries made. Suppose that the model equation is Y = -0.800 + 0.060x, + 0.900x2 + € (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? 5.8 v hr (b) How would you interpret ß1 = 0.060, the coefficient of the predictor X1? o When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a…arrow_forward
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