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CHAPTER 8 Basic Data Analysis for Quantitative Research ESSENTIALS OF MARKETING RESEARCH Hair/Wolfinbarger/Ortinau/Bush
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12-2 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Statistical Analysis Every set of data collected needs some summary information developed that describes the numbers it contains Central tendency and dispersion, Relationships of the sample data, and Hypothesis testing
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12-3 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Mode Response Most Often Given to a QuestionMode Response Most Often Given to a Question Median Middle Value of a Rank Ordered DistributionMedian Middle Value of a Rank Ordered Distribution Measures of Central Tendency Mean Arithmetic Average
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12-4 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Measures of Central Tendency Each measure of central tendency describes a distribution in its own manner: for nominal data, the mode is the best measure. for ordinal data, the median is generally the best. for interval or ratio data, the mean is generally used.
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12-5 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Describes how close to the mean or other measure of central tendency, the rest of the values fall Measures of Dispersions Range Distance between the smallest and largest value in a set Standard Deviation Measure of the average dispersion of the values about the mean
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12-6 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Exhibit 12.3 Output for Measures of Dispersion
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12-7 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Univariate Tests of Significance Tests of one variable at a time z-test t-test Appropriate for interval or ratio data
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12-8 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Exhibit 12.4 Univariate Hypothesis Test Using X16
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12-9 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Bivariate Statistical Tests Compare characteristics of two groups or two variables Cross-tabulation with Chi-Square t-test to compare two means Analysis of variance (ANOVA) to compare three or more means
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12-10 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Exhibit 12.5 Cross-Tabulation
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12-11 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Chi-Square Analysis Chi-square analysis enables the Researcher to test for statistical significance between the frequency distributions of two or more nominally scaled variables in a cross-tabulation table to determine if there is any association between the variables
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12-12 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Exhibit 12.6 SPSS Chi- Square Crosstab Example
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12-13 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Comparing means Requires interval or ratio data The t-test is the difference between the means divided by the variability of random means The t-value is a ratio of the difference between the two sample means and the std error The t-test tries to determine if the difference between the two sample means occurred by chance
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12-14 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Exhibit 12.7 Comparing Two Means with Independent Samples t-Test
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12-15 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Exhibit 12.8 Paired Samples t-Test
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12-16 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Analysis of Variance Analysis of Variance (ANOVA) is a statistical technique that determines if three or more means are statistically different from each other The dependent variable must be measurable; either interval or ratio scaled The independent variable must be categorical “One-way ANOVA” means that there is only one independent variable
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12-17 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 F-Test The F-test is the test used to statistically evaluate the differences between the group means in ANOVA
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12-18 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Follow-up Tests Anova does not tell us where the significant differences lie – just that a difference exists Tukey Duncan Scheffe
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12-19 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Exhibit 12.9 Example ANOVA
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