Introduction to Statistics
Introduction to Statistics is a beginner-level online course from Coursera in Statistics. It is structured in 12 modules, over 14h 11m. Learners rate it 4.6/5 from 4.3K ratings on Coursera.
Part of our Statistics courses collection, where we compare it against 5 other courses.
Course highlights
| Provider | Coursera |
| Duration | 14h 11m |
| Level | Beginner |
| Mode | Self-paced |
| Language | English |
| Certificate | Yes — shareable certificate |
| Rating | 4.6★ (4.3K reviews) |
| Price | Check price |
About this course
This Introduction to Statistics course, offered by Stanford University on Coursera, teaches you core statistical thinking concepts. It begins with fundamental ideas like descriptive statistics for exploring data and then moves into methods for producing data and sampling. You will learn about probability, including normal approximation and the binomial distribution. The course also covers sampling distributions and the Central Limit Theorem, which are key for understanding statistical inference.
Further modules in this statistics course explore regression, confidence intervals, and tests of significance. You also study resampling techniques, the analysis of categorical data, and One-Way Analysis of Variance (ANOVA), along with multiple comparisons. The structured syllabus guides you through these topics, building your understanding step-by-step over its 14 hours and 11 minutes of content.
Upon completing this Introduction to Statistics, you will develop practical skills in statistical analysis and exploratory data analysis. You can perform statistical inference, understand various sampling methods, and conduct statistical hypothesis testing. The course equips you to analyze data, interpret descriptive statistics, and apply principles of probability and statistics to real-world scenarios. You also gain abilities in statistical visualization and correlation analysis, essential for presenting data insights effectively.
This course is designed for beginners and does not require calculus, making it accessible to a wide audience. However, this also means it focuses on conceptual understanding rather than deep mathematical proofs. If your goal is to learn statistics using specific software, this course provides the foundational theory but does not include software tutorials. For instance, if you want to learn with a tool like SPSS, consider Explore Basic Statistics With IBM SPSS STATISTICS on Udemy.
If you are interested in how statistics apply to specific fields, or need a broader program, other options are available. For those focusing on social sciences, Methods and Statistics in Social Sciences by Coursera offers a related specialization. For another free beginner-level statistics course, you can explore the Free Intro Statistics Course | Udacity. If your interest lies in educational contexts, Basics of Statistics In Education on Udemy is another free option.
Level and time commitment
- Basic familiarity with computers and productivity software
- No calculus required
Skills you’ll gain
What this course covers
12 modulesThe 12-part outline Coursera publishes for this course, across 14h 11m.
Module 1 · Introduction and Descriptive Statistics for Exploring Data
Module 2 · Producing Data and Sampling
Module 3 · Probability
Module 4 · Normal Approximation and Binomial Distribution
Module 5 · Sampling Distributions and the Central Limit Theorem
Module 6 · Regression
Module 7 · Confidence Intervals
Module 8 · Tests of Significance
Module 9 · Resampling
Module 10 · Analysis of Categorical Data
Module 11 · One-Way Analysis of Variance (ANOVA)
Module 12 · Multiple Comparisons
What learners rate it
Rated 4.6/5 by 4.3K learners on Coursera (checked 10 Aug 2026).
This rating is collected by Coursera from its own enrolled learners. We reproduce it as reported and do not accept paid or incentivised reviews. See it on Coursera →
Compiled by the CoursesGlobal editorial desk. Fees, ratings, duration and certificate details for the 1 course shown are read directly from Coursera course pages — we never estimate a price or a rating. Last verified 10 August 2026.
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Compare with alternatives
Same topic, different trade-offs — here's who runs each one and what it's best at.
| Course | Provider | Rating | Price | Duration | Why pick this one |
|---|---|---|---|---|---|
| Introduction to Statistics This |
 Coursera
|
4.6★ | Check price | 14h 11m | Quickest to finish (14h 11m) |
| Methods and Statistics in Social Sciences |
Coursera
|
4.6★ | Check price | 3 months | Highest rated (4.6★ from 8K reviews) |
| Free Intro Statistics Course | Udacity | Udacity | 4.5★ | Free | Free to audit | |
| Basics of Statistics In Education |
 Udemy
|
4.4★ | Free | Free — and still gives a certificate |
Where Statistics leads
Roles we map to Statistics on CoursesGlobal. This is our own mapping of subject to job, not a placement claim by Coursera.
Browse every course we track for one of these — courses for data analysts.
Common questions
How much does Introduction to Statistics cost?
Coursera does not publish a price we can read on the course page, so we do not show one. Check the fee on the provider site — we would rather say nothing than quote a number we did not collect.
Does Introduction to Statistics come with a certificate?
Yes — Coursera lists a certificate on completion. It is a course certificate, not a formal qualification or university credit.
How long does Introduction to Statistics take?
Coursera lists it at 14h 11m. It is self-paced, so that is the volume of material rather than a deadline — how long it actually takes depends on the hours you put in each week.
Is Introduction to Statistics suitable for beginners?
Yes. Coursera lists it at Beginner level, so no prior experience in the subject is assumed.
What does Introduction to Statistics cover?
It is organised into 12 modules, starting with Introduction and Descriptive Statistics for Exploring Data and going on to Producing Data and Sampling, Probability, Normal Approximation and Binomial Distribution, Sampling Distributions and the Central Limit Theorem, among others. The full outline is on this page.