Johns Hopkins University · on Coursera

Statistical Inference

4.4(12,000) on Coursera·380K enrolled
Intermediate 54 hours English Specialization
Our recommendation
Johns Hopkins' Statistical Inference course, part of its Data Science specialisation. It covers the core of statistical reasoning — probability, hypothesis testing, confidence intervals and Bayesian ideas. It is rigorous and mathematical, a strong foundation for serious data work rather than a gentle intro.

Good for: Data learners who want a rigorous grounding in statistical inference.

Less suitable if: You want a gentle, applied-only course, or you are uncomfortable with maths.

Skills you'll gain

StatisticsHypothesis testingConfidence intervalsProbabilityBayesian statisticsStatistical inference

Is this course right for you?

A good fit if you…

You want rigorous statistics
You are comfortable with maths
You are heading into data science

Consider something else if you…

You want a gentle intro
You are uncomfortable with maths
You want applied coding only

Requirements: Some statistics and maths comfort; intermediate.

Realistic time: About 54 hours; a few weeks part-time.

About this course

Part of the Johns Hopkins Data Science Specialization, this course covers statistical inference from first principles: probability theory, expected values and variance, common distributions, the central limit theorem, confidence intervals, hypothesis tests, and p-values.

What you'll learn

Calculate probabilities using common statistical distributions
Apply the central limit theorem to make inferences about populations
Construct and interpret confidence intervals correctly
Perform and interpret hypothesis tests including t-tests and chi-square tests
Recognize and avoid common statistical inference mistakes

This course includes

54h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language

What it costs

Free to audit on Coursera; the certificate needs a subscription (about $49 a month), with financial aid available.

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Is the certificate recognised?

Issued through Coursera with Johns Hopkins, part of its Data Science series. The understanding is the value.

Instructor

BC
Brian Caffo / Roger Peng
Coursera instructor
380K+ learners10 courses4.4 instructor rating

Taught by Brian Caffo, Johns Hopkins biostatistics professor and prolific Coursera instructor known for rigorous yet accessible statistical education.

About this provider

CO
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Frequently asked questions

Yes for a rigorous grounding in the statistics behind data science. It is more demanding than a gentle intro.
It is mathematical and rigorous, but well taught. Expect real effort.
You can audit it free on Coursera; the certificate needs a subscription, with financial aid available.
Yes. It is part of Johns Hopkins' Data Science specialisation.
Some comfort with statistics and maths. It is pitched at intermediate level.
Paid
Free to audit, paid certificate
Enroll now