Inferential Statistics
Skills:
ML Maths Basics90%
This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: ML Maths Basics
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
Managing Relational Bottlenecks: A Technical Audit of Advanced Academic Database Support Systems
Medium · Data Science
Building a Production-Ready Snowflake MCP Server
Hackernoon
The Privacy Bill Always Comes Due — Joseph Sides
Medium · AI
How I Prepared for a Data Science Aptitude Test for a German Master’s Program
Medium · Data Science
🎓
Tutor Explanation
DeepCamp AI