This course covers making inferences from sample data to the broader population. It delves into the principles of significance testing, including p-values, power, and Type I and II errors, and covers a wide range of statistical tests for different data types and research designs.
Build the mathematical foundation for ML with free courses from MIT, 3Blue1Brown, and fast.ai. Covers linear algebra, calculus, statistics, and probability.
Build the mathematical foundation essential for ML. Master linear algebra, calculus, probability, and statistics—the core concepts powering every machine learning algorithm.
Log in to write a review
Loading reviews...
Explore more courses and learning paths related to Inferential Statistics.
Browse more courses from Coursera
See the side-by-side breakdown and our pick by scenario
See the side-by-side breakdown and our pick by scenario
More intermediate-level AI and ML courses
Follow the full Free Math for Machine Learning learning path
Browse 350+ structured AI learning paths from beginner to advanced
Provided by Coursera
Pricing: Free to audit, paid certificate
Free to audit. Certificate: $49-79. Coursera Plus: $59/month