Question 1 Select all of the answers that should be included when using a table to report the results from the following regression test: Model R Square Adjusted R Square Std. Error of the Estimate 065 .004 -.039 1.577 a. Predictors: (Constant), How old (in years) were you when you delivered? ANOVA³ Model Sum of Squares df Mean Square F Sig. Regression .243 1 .243 .098 .757b 1 Residual 57.197 23 2.487 Total 57.440 24 a. Dependent Variable: At what gestational age was your baby born? b. Predictors: (Constant), How old (in years) were you when you delivered? Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) 40.017 2.253 17.759 .000 1 How old (in years) were you when you -.025 delivered? .079 -.065 -.313 .757 1. Beta: 065 2. Coefficient B of the Constant: 40.017 3. R: 065 4. Sums of Squares of the Residual: 57.197 5. F score: 28 Beta: -065 Sums of Squares of the Residual: 57.197 Coefficient B of the Constant: 40.017 F score: 098 R:.065

Question 1 Select all of the answers that should be included when using a table to report the results from the following regression test: Model R Square Adjusted R Square Std. Error of the Estimate 065 .004 -.039 1.577 a. Predictors: (Constant), How old (in years) were you when you delivered? ANOVA³ Model Sum of Squares df Mean Square F Sig. Regression .243 1 .243 .098 .757b 1 Residual 57.197 23 2.487 Total 57.440 24 a. Dependent Variable: At what gestational age was your baby born? b. Predictors: (Constant), How old (in years) were you when you delivered? Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) 40.017 2.253 17.759 .000 1 How old (in years) were you when you -.025 delivered? .079 -.065 -.313 .757 1. Beta: 065 2. Coefficient B of the Constant: 40.017 3. R: 065 4. Sums of Squares of the Residual: 57.197 5. F score: 28 Beta: -065 Sums of Squares of the Residual: 57.197 Coefficient B of the Constant: 40.017 F score: 098 R:.065

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...

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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?
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 accuracy
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