Statistics for Data Science II
A comprehensive course on inferential statistics, covering probability distributions, estimation, and hypothesis testing.
Statistics for Data Science II
Course Overview
This course builds upon the foundational concepts of probability and statistics introduced in Statistics I. It focuses on inferential statistics, enabling you to draw conclusions about populations based on sample data.
Key Topics
- Random Variables: Discrete and Continuous, Joint Distributions.
- Estimation: Point estimation (MLE, MOM) and Interval estimation.
- Hypothesis Testing: Testing for means, variances, and proportions.
- Regression: Simple Linear Regression.
Course Structure
The course is divided into 12 weeks, with a mix of theoretical lessons, practice quizzes, and graded assignments.
| Week | Topic |
|---|---|
| Week 1 | Random Variables & Expectations |
| Week 2 | Joint Distributions |
| Week 3 | Continuous Random Variables |
| Week 4 | Sampling Distributions |
| … | … |
Select a week from the sidebar to begin your learning journey.