The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Predictor Coef SE Coef t-ratio Constant -7.611 2.567 0.186 0.035 2.965 0.046 Arm span - 5.377 0.000 S = 1.61 R-Sq 63.0% R-Sq (Adj) = 64.9% Which of the following is the best interpretation of the coefficient of determination 2? O About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. O About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. O About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. O About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.

The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Predictor Coef SE Coef t-ratio Constant -7.611 2.567 0.186 0.035 2.965 0.046 Arm span - 5.377 0.000 S = 1.61 R-Sq 63.0% R-Sq (Adj) = 64.9% Which of the following is the best interpretation of the coefficient of determination 2? O About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. O About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. O About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. O About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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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?
The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenueas a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly GrossRevenue($1000s) Television Advertising($1000s) Newspaper Advertising($1000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 a. Develop an estimated regression equation with the amount of televisionadvertising as the independent variable.b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. c. Is the estimated regression equation coefficient for television advertisingexpenditures the same in part (a) and in part (b)? Interpret the coefficient in each case. d. Predict weekly gross revenue for a week when $3500 is spent on television advertising and $1800 is spent on newspaper advertising.
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