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12: Basic Data Analysis for Quantitative Research
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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 Summary Statistics 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 only possible 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 Dispersion 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 SPSS 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 Hypothesis Testing Independent Samples two or more groups of responses that are tested as though they come from different populations Related (Matched) Samples two or more groups of responses that are assumed to originate from the same population
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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 Univariate Tests of Significance Tests of one variable at a time z-test t-test Appropriate for interval or ratio data Test: “Is a mean significantly different from some number?”
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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 Univariate Hypothesis Test Using X16 Variable (Reasonable Prices)
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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 Bivariate Statistical Tests Compare characteristics (means or frequencies) 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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12-11 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Cross-Tabulation: Ad Recall vs. Gender
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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 Chi-Square Analysis Chi-square analysis enables the researcher to test for statistical significance between the frequency distributions of two or more nominally scaled (i.e. “categorical”) variables in a cross-tabulation table to determine if there is any association between the variables
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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 SPSS Chi-Square Crosstab Example
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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 Comparing means Requires interval or ratio data The t-test is the difference between the means divided by the average variability of the two random means The t-value is a ratio of the difference between the two sample means and the std error of the difference in means The t-test tries to determine whether the difference between the two sample means is significant or whether it occurred by chance
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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 Comparing Two Means with Independent 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 Comparing Two Means with Paired Samples t-Test
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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 Analysis of Variance ANOVA determines whether three or more means are statistically different from each other The dependent variable must be either interval or ratio data The independent variable(s) must be categorical (i.e. nominal or ordinal) “One-way ANOVA” means that there is only one independent variable
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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 F-Test The F-test is the test used to statistically evaluate the differences between the group means in ANOVA
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12-19 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Total variance in dataset can be separated into Between Group and Within Group Variance. Total variance in dataset can be separated into Between Group and Within Group Variance. The larger the variance Between Groups vs. Within Groups, the larger the F-Ratio. The larger the variance Between Groups vs. Within Groups, the larger the F-Ratio. The higher the F-Ratio, the more likely it is that the Null Hypothesis will be rejected and that the means are statistically different. The higher the F-Ratio, the more likely it is that the Null Hypothesis will be rejected and that the means are statistically different. Determining Statistical Significance using F-Test
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12-20 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 SPSS One-way ANOVA example: Likelihood of Recommending vs. Gender
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12-21 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 Pairwise Comparison Tests Tukey Duncan Scheffe
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12-22 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 SPSS Scheffe Test Example
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12-23 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 n-way ANOVA Appropriate for multiple independent variables Example: men and women are shown humorous and non-humorous ads and then attitudes toward brand are measured. IVs = (1) gender, and (2) ad type; DV = attitude toward brand Need 2-way ANOVA design here (also called “factorial design”) because we have 2 IVs
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12-24 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 SPSS Example: 2-way ANOVA Likelihood of Recommending vs. (1) Gender & (2) Distance
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12-25 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 SPSS Example: Repeated Measures ANOVA Does your version of SPSS have it?
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