Methods

We provide additional material for each method to ease the understanding and to improve your learning experience.

Fact sheet

Fact sheets summarize the main facts about a specific method

Table of content

Check the TOC of the corresponding book chapter

Excel example

Run your first multivaraite analysis with the help of Excel

R code + output

R code and output for the chocolate case study

Test your knowledge

Quizzes to test your knowledge

SPSS data set

Order the SPSS data set + syntax used in the book

Lecturer support

We offer lecturer slides as well as all tables and figures

Videos

We plan to offer videos to ease the understanding of specific issues

Basics of Data Analysis

The introduction serves as a refresher and reference to basic statistical measures.

Regression Analysis is the most frequently used method of multivariate analysis.

Analysis of Variance (ANOVA) is frequently used to analysis experimental data.

Discriminant Analysis aims to identify differences across groups.

Logistic regression is suited if the dependent variable is categorical.

Contingency analysis tests whether categorical variables are associated.

Factor analysis reduces a large number of variables to a smaller number of factors.

Cluster analysis groups subjects or objects that are similar.

Conjoint analysis measures preferences and attribute importance for products.

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Methods
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