Statistics is the study of how best to collect, analyze, and draw conclusions from data. A strong foundation will serve you well, no matter what industry you work in. In this beginner’s track, you'll learn the concepts, topics, and techniques used by data scientists and statisticians every day—including observational studies and experiments, correlation, regression, exploratory data analysis, and inference. You’ll also develop your stats skills by working with real-world data, including Stack Overflow surveys, real estate prices, and medical shipment data. Start this track today to learn about the power of statistics and how it can be used in your day-to-day analyses!
Overview
Syllabus
- Introduction to Statistics in R
- Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.
- Introduction to Regression in R
- Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
- Intermediate Regression in R
- Learn to perform linear and logistic regression with multiple explanatory variables.
- Sampling in R
- Master sampling to get more accurate statistics with less data.
- Hypothesis Testing in R
- Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
- Hypothesis Testing with Men's and Women's Soccer Matches
Taught by
Maggie Matsui and Richie Cotton
