Data Science Basics

Intro to data science applied to Software Engineering problems. Refresher/intro to data science concepts and tools.

Learning Outcomes

• position data science in the scope of SE activities
• refresh knowledge of basic statistical approaches
• re-examine concepts on regression and interpretation of coefficients

Topics and slides

These are the submodules I covered in class.

• Data Mining Basics include search and optimize
• Regression (notebook)

Readings

1. Confusion matrices - Wikipedia
2. R for Data Science - Tidy Data
3. EDA in R
4. Regression intro/overview, ROS ch 6.1-6.5

Exercises

These are done in class. The source code below is a combo of what I typed and what I prepped before hand.

1. Basic data exploration
2. P-value displays
3. Run glm

Optional Readings and Activities

These readings enrich the material but are not strictly necessary to read.

1. Quarto overview