DATA220 - Research Methods in Data Science

Fall 2

Course Description

This course covers research methods in data science. The emphasis of this course is on developing the habits of sound critical thinking.

Weekly Projects

1. Guide to Evaluate Your Own Research Question

Evaluated research topics and refined goals and questions.

View Report

2. Design an Experiment

Developed methodology addressing confounding variables.

View Report

3. Creating a Sample Survey

Survey assessing student interest in sports programs.

View Report

4. Simulating With Distributions

R project simulating data distributions with visual and statistical summaries.

View Report

5. Cleaning Data

Cleaned GDP and population data, handling missing values.

View Report

6. Exploring Data

Cleaned GDP and population data for analysis.

View Report

7. Distribution Project: Quality Control Process

Analyzed widget defects and size distribution.

View Report

8. Hypothesis Testing Project: Apps

Quality control analysis of manufacturing standards.

View Report

9. t-Test Project: Customer Satisfaction

Analyzed customer satisfaction across membership types.

View Report

10. Linear Regression: Ice Cream Sales & Glucose

Two-part analysis on temperature effects and glucose levels.

View Report

11. Can We Predict Education Levels Based On Livability?

Explores factors influencing higher education pursuit.

View Report

12. Bad Santa Regression Project

Examines potential gender bias in gift-giving patterns.

View Report

Final Project

Chess's Impact on Memory

Explored whether chess mastery requires innate intelligence or develops through memory enhancement, examining whether regular chess engagement improves memory in young adults using simulated fall-semester data from The Islands platform.

Read the full writeup