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Chapter 10: Q1BSC (page 468)

\({s_e}\)Notation Using Data Set 1 鈥淏ody Data鈥� in Appendix B, if we let the predictor variable x represent heights of males and let the response variable y represent weights of males, the sample of 153 heights and weights results in\({s_e}\)= 16.27555 cm. In your own words, describe what that value of \({s_e}\)represents.

Short Answer

Expert verified

The value of \({s_e}\) equal to 16.27555 cm explains that the average distance of the observed value of weights of males from the fitted values is obtained using the regression equation.

Step by step solution

01

Given information

A regression equation between the response variable 鈥渨eights of male鈥� and the predictor variable 鈥渉eights of males鈥� is given.

The value of \({s_e}\) is 16.27555 cm.

02

Meaning of \({s_e}\)

\({s_e}\)stands for the standard error of the estimate.

It describes the mean distance between the observed values of the response variable and the predicted values.

Here, the response variable is the weights of males, and the standard error of the estimate\(\left( {{s_e}} \right)\)is 16.27555 cm.

Thus, the standard error of estimate tells that the average difference between the measured weights and the weights predicted by the regression equation equals 16.27555 cm.

It represents how much the sample points deviate from the regression line.

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Most popular questions from this chapter

Testing for a Linear Correlation. In Exercises 13鈥�28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of A = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.)

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x

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