Methodology tutorial - exploratory data analysis

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This is part of the methodology tutorial (see its table of contents).

Introduction

This tutorial is a short introduction to simple multi-variate exploratory data analysis. There exist many techniques, here we just introduce cluster analysis and Factor Analysis (principal components).

Learning goals

• Be able to select a procedure for exploratory data analysis
• ........

Prerequisites

• Methodology tutorial - quantitative data analysis

Moving on

• none

Level and target population

• Beginners

Quality

• Under construction , use with care !!

Cluster Analysis

• Cluster analysis or classification refers to a set of multivariate methods for grouping elements (subjects or variables) from some finite set into clusters of similar elements (subjects or variables).

• There different kinds of cluster analysis. The most popular are : hierarchical cluster analysis and K-means cluster.

Typical use case examples: Classify teachers into 4 to 6 different groups regarding ICT usage

Hierarchical cluster analysis

Tries to identify similar cases in progressive steps. This procedure allows to produce a dendogram (tree diagram of the population)

Example

classification of teachers

• A hierarchical analysis of 36 survey variables allowed to identify 6 major types of teachers with respect to ICT use:
• Type 1 : The "convinced teacher" (l’enseignant convaincu)
• Type 2 : The "active teacher" (les enseignants actifs)
• Type 3 : The "motivated teacher working within a bad environment" (les enseignants motivés ne disposant pas d’un environnement favorable)
• Type 4 : The "willing but not ICT-compentent teacher" (les enseignants volontaires, mais faibles dans le domaine des technologies(
• Type 5 : The "ICT-competent teacher unwilling to use ICT in the class" (l’enseignant techniquement fort mais peu actif en TIC)
• Type 6 : The "Willing and relatively weak in ICT teacher" (l’enseignant à l’aise malgré un niveau moyen de maîtrise)

In order to come up with such labels like "convinced teacher" you have to list the means of all cluster variables and use your imagination.

Descriptive statistics of a subset of the 36 variables used for analysis:

(sorry this is hardly readable)