Slide 14-1

Copyright © 2012, 2008, 2005 Pearson

Education, Inc.

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Chapter 14

Descriptive Methods in

Regression and Correlation

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Section 14.1

Linear Equations with One Independent Variable

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Definition 14.1

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Section 14.2

The Regression Equation

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Table 14.2 Age and price

data for a sample

of 11 Orions

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Scatterplot for the

age and price data

of Orions from

Table 14.2

Figure 14.7

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Table 14.3 & Figure 14.8

Scatterplot for the data points in Table 14.3

Four data points

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Figure 14.9Two possible lines to fit the data points in Table 14.3

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Table 14.4Determining how well the data points in Table 14.3 are fit

by (a) Line A and (b) Line B

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Key Fact 14.2 & Definition 14.2

Least-Squares Criterion

The least-squares criterion is that the line that best

fits a set of data points is the one having the smallest

possible sum of squared errors.

Regression Line and Regression Equation

Regression line: The line that best fits a set of data

points according to the least-squares criterion.

Regression equation: The equation of the

regression line.

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Definition 14.3

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Formula 14.1

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Table 14.5Table for computing

the regression

equation for the

Orion data

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Figure 14.10Regression line and

data points for

Orion data

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Figure 14.11Extrapolation in

the Orion example

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Figure 14.12Regression lines with

and without the influential

observation removed

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Section 14.3

The Coefficient of Determination

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Definition 14.5

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Table 14.6 Table for

computing SST

for the Orion

price data

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Table 14.7Table for

computing

SSR for the

Orion price

data

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Table 14.8Table for

computing SSE

for the Orion

data

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Section 14.4

Linear Correlation

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Definition 14.7 & Formula 14.3

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Figure 14.17Various degrees of linear

correlation