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Effects of Clusters Refer to the Minitab-generated scatterplot given in Exercise 12 of Section 10-1 on page 485.

a. Using the pairs of values for all 8 points, find the equation of the regression line.

b. Using only the pairs of values for the 4 points in the lower left corner, find the equation of the regression line.

c. Using only the pairs of values for the 4 points in the upper right corner, find the equation of the regression line.

d. Compare the results from parts (a), (b), and (c).

Short Answer

Expert verified

a. The regression equation is\(\hat y = 0.085 - 0.985x\).

b. The regression equation with only 4 lower-left corner values is\(\hat y = 1.5 - 0.00x\).

c. The regression equation with only 4 upper-right corner values is\(\hat y = 9.5 - 0.00x\).

c. The regression equations obtained in parts (a), (b), and (c) are completely different from one another. The presence of different sets of values affects the regression equation to a large extent.

Step by step solution

01

Given information

A set of 8 pairs of values is considered.

02

Regression equation using all values

a.

The regression equation of y on x has the following notation:

\(\hat y = {b_0} + {b_1}x\),where

\({b_0}\)is the intercept term, and

\({b_1}\) is the slope coefficient.

The following data points are considered:

The following table shows the necessary calculations:


The value of the y-intercept is computed below.

\(\begin{array}{c}{b_0} = \frac{{\left( {\sum y } \right)\left( {\sum {{x^2}} } \right) - \left( {\sum x } \right)\left( {\sum {xy} } \right)}}{{n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}}}\\ = \frac{{\left( {44} \right)\left( {372} \right) - \left( {44} \right)\left( {370} \right)}}{{8\left( {372} \right) - {{\left( {44} \right)}^2}}}\\ = 0.085\end{array}\).

The value of the slope coefficient is computed below.

\(\begin{array}{c}{b_1} = \frac{{n\left( {\sum {xy} } \right) - \left( {\sum x } \right)\left( {\sum y } \right)}}{{n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}}}\\ = \frac{{\left( 8 \right)\left( {370} \right) - \left( {44} \right)\left( {44} \right)}}{{8\left( {372} \right) - {{\left( {44} \right)}^2}}}\\ = 0.985\end{array}\).

03

Regression equation using only lower-left points

b.

The following 4 pairs of data points are considered:

The following table shows the necessary calculations:

The value of the y-intercept is computed below.

\(\begin{array}{c}{b_0} = \frac{{\left( {\sum y } \right)\left( {\sum {{x^2}} } \right) - \left( {\sum x } \right)\left( {\sum {xy} } \right)}}{{n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}}}\\ = \frac{{\left( 6 \right)\left( {10} \right) - \left( 6 \right)\left( 9 \right)}}{{4\left( {10} \right) - {{\left( 6 \right)}^2}}}\\ = 1.5\end{array}\).

The value of the slope coefficient is computed below.

\(\begin{array}{c}{b_1} = \frac{{n\left( {\sum {xy} } \right) - \left( {\sum x } \right)\left( {\sum y } \right)}}{{n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}}}\\ = \frac{{\left( 4 \right)\left( 9 \right) - \left( 6 \right)\left( 6 \right)}}{{4\left( {10} \right) - {{\left( 6 \right)}^2}}}\\ = 0.000\end{array}\).

Thus, the regression equation becomes

\(\hat y = 1.5 - 0.00x\).

04

Regression equation using upper-right corner values

c.

The following 4 pairs of data points are considered:

The following table shows the necessary calculations:

The value of the y-intercept is computed below.

\(\begin{array}{c}{b_0} = \frac{{\left( {\sum y } \right)\left( {\sum {{x^2}} } \right) - \left( {\sum x } \right)\left( {\sum {xy} } \right)}}{{n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}}}\\ = \frac{{\left( {38} \right)\left( {362} \right) - \left( {38} \right)\left( {361} \right)}}{{4\left( {362} \right) - {{\left( {38} \right)}^2}}}\\ = 9.5\end{array}\).

The value of the slope coefficient is computed below.

\(\begin{array}{c}{b_1} = \frac{{n\left( {\sum {xy} } \right) - \left( {\sum x } \right)\left( {\sum y } \right)}}{{n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}}}\\ = \frac{{\left( 4 \right)\left( {361} \right) - \left( {38} \right)\left( {38} \right)}}{{4\left( {362} \right) - {{\left( {38} \right)}^2}}}\\ = 0.000\end{array}\).

Thus, the regression equation becomes

\(\hat y = 9.5 - 0.00x\).

05

Comparison

d.

The regression equations obtained in parts (a), (b), and (c) are completely different from one another.

Thus, the presence of different sets of values can greatly influence the regression equation.

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Most popular questions from this chapter

In exercise 10-1 12. Clusters Refer to the following Minitab-generated scatterplot. The four points in the lower left corner are measurements from women, and the four points in the upper right corner are from men.

a. Examine the pattern of the four points in the lower left corner (from women) only, and subjectively determine whether there appears to be a correlation between x and y for women.

b. Examine the pattern of the four points in the upper right corner (from men) only, and subjectively determine whether there appears to be a correlation between x and y for men.

c. Find the linear correlation coefficient using only the four points in the lower left corner (for women). Will the four points in the upper left corner (for men) have the same linear correlation coefficient?

d. Find the value of the linear correlation coefficient using all eight points. What does that value suggest about the relationship between x and y?

e. Based on the preceding results, what do you conclude? Should the data from women and the data from men be considered together, or do they appear to represent two different and distinct populations that should be analyzed separately?

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a. Construct a scatterplot.

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x

10

8

13

9

11

14

6

4

12

7

5

y

9.14

8.14

8.74

8.77

9.26

8.10

6.13

3.10

9.13

7.26

4.74

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