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Coursera

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 1 other course.

★★★★★4.6(4.3K reviews) English

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 Free

Level and time commitment

Coursera lists this course at Beginner level.
No prior experience in the subject is assumed — this is where the provider expects a newcomer to start.
What the provider says you need first:
  • Basic familiarity with computers and productivity software
  • No calculus required
Time commitment: 14h 11m.
It is self-paced, so that figure is the material, not a fixed schedule.

Skills you’ll gain

Statistical AnalysisExploratory Data AnalysisStatistical InferenceSampling (Statistics)Statistical Hypothesis TestingData AnalysisDescriptive StatisticsProbability & StatisticsAnalysisStatistical VisualizationStatisticsCorrelation Analysis

What this course covers

12 modules

The 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

4.6
★★★★★
4.3K ratings

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 →

How this page is put together

Compiled by the 10courses 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.

How we compare and rank courses · Our review policy · Affiliate disclosure

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 Highest rated (4.6★ from 4.3K reviews)
Learn Python 2 Codecademy 4.3★ Free 17h Free — and still gives a certificate
See all Statistics courses →

Where Statistics leads

Roles we map to Statistics on 10courses. This is our own mapping of subject to job, not a placement claim by Coursera.

Data Analyst Data Scientist

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.