This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes

Overview

Automating-Ridit-Analysis

This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes, with the question response being on likert scale.

For instance, this dataset is about the university faculty perceptions and practices of using Wikipedia as a teaching resource. The university faculties have many interesting attributes such as age, gender, years of expericence, their domain of expectrice, etc... . This survey also has many questions which makes the job of comprehensively analysing the data difficult. This repository is a simple illustration of how to go about automating this tedious task.

Data Source:

Meseguer-Artola, Antoni & Aibar, Eduard & Lladós-Masllorens, Josep & Minguillón, Julià & Lerga, Maura. (2016). Factors that influence the teaching use of Wikipedia in Higher Education. Journal of the Association for Information Science and Technology. 67. 1224-1232. 10.1002/asi.23488.

The data used was found at: https://archive.ics.uci.edu/ml/datasets/wiki4he

Owner
Ishan Hegde
Ishan Hegde
Project under the certification "Data Analysis with Python" on FreeCodeCamp

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