Course description
Introduction to Statistics
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.
Do you work at this organisation and want to update this page?
Is there out-of-date information about your organisation or courses published here? Fill out this form to get in touch with us.
Upcoming start dates
Suitability - Who should attend?
- Basic familiarity with computers and productivity software
- No calculus required
Training Course Content
- Introduction and Descriptive Statistics for Exploring Data
- Producing Data and Sampling
- Probability
- Normal Approximation and Binomial Distribution
- Sampling Distributions and the Central Limit Theorem
- Regression
- Confidence Intervals
- Tests of Significance
- Resampling
- Analysis of Categorical Data
- One-Way Analysis of Variance (ANOVA)
- Multiple Comparisons
Course delivery details
This course is offered through Stanford University, a partner institute of Coursera.
Expenses
Please visit the Institute website for more information about tuition fees