Statistical-Inference-on-Learning-Methods-Using-Python

The main objective of this project is to use Python's Pandas and Scipy libraries to implement statistical inferences on the acquired survey data.

Steps included

1. Organized data by transforming the Likert Scale results to encodable data
2. Use pandas to generate transformations in the data set regarding the multiple choice options in the survey data
3. Use stats to acquire statistical summariese of the different assigned groups
4. Visualize data and gather all important statistical measures

Comparing Active Vs Passive Learning

There are 3 groups that were created based on the learning styles that the students mentioned during their online classes.

Based on these groupings, the students were surveyed using a 5-point Likert Scale that answers these multiple aspects of perception on online classes:

1. I enjoy having courses online (Class Enjoyment)
2. I feel the motivation to learn (Motivation to Learn)
3. I am satisfied with the instruction of my online courses (Course Satisfaction) My courses are engaging (Course Engagement)
4. I am often distracted when doing coursework or attending classes (Ability to Focus in Class)
5. I often ask questions, comment, join discussions (Class participation)

Based on these results, we compared each of the group to determine significant differences and analyze the underlying reasons of the acquired results.