Research Methods, William G. Zikmund, Ch24

34
Business Research Methods William G. Zikmund Chapter 24 Multivariate Analysis

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Research Methods William G. Zikmund

Transcript of Research Methods, William G. Zikmund, Ch24

Page 1: Research Methods, William G. Zikmund, Ch24

Business Research Methods

William G. Zikmund

Chapter 24

Multivariate Analysis

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Multivariate Statistical Analysis

• Statistical methods that allow the simultaneous investigation of more than two variables

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All multivariatemethods

Are some of thevariables dependent

on others?

Yes No

Dependencemethods

Interdependencemethods

A Classification of Selected Multivariate Methods

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Dependence Methods

• A category of multivariate statistical techniques; dependence methods explain or predict a dependent variable(s) on the basis of two or more independent variables

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DependenceMethods

How manyvariables aredependent

One dependentvariable

Severaldependentvariables

Multipleindependent

and dependentvariables

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DependenceMethods

How manyvariables aredependent

One dependentvariable

NonmetricMetric

Multiplediscriminant

analysis

Multipleregression

analysis

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DependenceMethods

How manyvariables aredependent

NonmetricMetric

Conjointanalysis

Multivariateanalysis of

variance

Severaldependentvariables

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DependenceMethods

How manyvariables aredependent

Multipleindependent

and dependentvariables

Metricor

nonmetric

Canonicalcorrelation

analysis

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Interdependence Methods

• A category of multivariate statistical techniques; interdependence methods give meaning to a set of variables or seek to group things together

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Interdependencemethods

Are inputs metric?

Metric Nonmetric

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Metric

Metricmultidimensional

scaling

Clusteranalysis

Factoranalysis

Interdependencemethods

Are inputs metric?

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Nonmetric

Nonmetric

Interdependencemethods

Are inputs metric?

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Multiple Regression

• An extension of bivariate regression

• Allows for the simultaneous investigation– two or more independent variables– a single interval-scaled dependent variable

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Y= aX1X2X3...nXn

Multiple Regression Equation

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2211 XXaY

nnXX .....33

Multiple Regression Analysis

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Coefficients of Partial Regression

Independent variables correlated with one another

The % of the variance in the dependent variable that is explained by a single independent variable, holding other independent variables constant

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Coefficient of Multiple Determination

• R2

• The % of the variance in the dependent variable that is explained by the variation in the independent variables.

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• Y = 102.18 + .387X1 + 115.2X2 + 6.73X3

• Coefficient of multiple determination (R2) .845

• F-value 14.6

Statistical Results of a Multiple Regression

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1/

/

knSSe

kSSrF

F-Test

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Degrees of Freedom (d.f.) are Calculated as Follows:

• d.f. for the numerator = k

• for the denominator = n - k - 1

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Degrees of Freedom

• k = number of independent variables

• n = number of observations or respondents

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where

        k = number of independent variables

        n = number of observations

)1/()(/)(

knSSekSSr

F

F-test

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Multiple Discriminant Analysis

• A statistical technique for predicting the probability of objects belonging in two or more mutually exclusive categories (dependent variable) based on several independent variables

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Zi = b1X1i + b2X2i + . . . + bnXni

• where

• Zi = ith applicant’s discriminant score

• bn = discriminant coefficient for the nth variable

• Xni = applicant’s value on the nth independent variable

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iii XbXbZ 2211 ninXb ........

Discriminant Analysis

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= applicant’s value on the jth independent variable

= discriminant coefficient for the jth variable

= ith applicant’s discriminant score

jiX

jb

iZ

Discriminant Analysis

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Canonical Correlation

• Two or more criterion variables (dependent variables)

• Multiple predictor variables (independent variables)

• An extension of multiple regression

• Linear association between two sets of variables

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Canonical Correlation

• Z = a1X1 + a2X2 + . . . + anXn

• W = b1Y1 + b2Y2 + . . . + bnYn

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Factor Analysis

• Summarize the information in a large number of variables

• Into a smaller number of factors

• Several factor-analytical techniques

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Factor Analysis

• A type of analysis used to discern the underlying dimensions or regularity in phenomena. Its general purpose is to summarize the information contained in a large number of variables into a smaller number of factors.

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Height

Weight

Occupation

Education

Source ofIncome

Size

Social Status

Factor Analysis

Copyright © 2000 Harcourt, Inc. All rights reserved.

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Cluster Analysis

• A body of techniques with the purpose of classifying individuals or objects into a small number of mutually exclusive groups, ensuring that there will be as much likeness within groups and as much difference among groups as possible

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Multidimensional Scaling

• A statistical technique that measures objects in multidimensional space on the basis of respondents’ judgments of the similarity of objects

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Multivariate Analysis of Variance (MANOVA)

• A statistical technique that provides a simultaneous significance test of mean difference between groups for two or more dependent variables