Stanford’s “Introduction to Statistics” teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.
Topics include Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons.
Introduction to Statistics | Stanford University Summary
- Offered by: Stanford University
- Instructor: Guenther Walther (Professor of Statistics)
- Cetification: Shareable Certificate (Earn a Certificate upon completion)
- Mode: 100% online Flexible deadlines
- Medium: English
- Number of Hours: Approx. 15 hours to complete
Introduction to Statistics | Stanford University Syllabus
- Introduction and Descriptive Statistics for Exploring Data
- Producing Data and Sampling
- Normal Approximation and Binomial Distribution
- Regression
- Confidence Intervals
- Resampling
- One-Way Analysis of Variance (ANOVA)
- Multiple Comparisons
