Harvard STAT 111: Introduction to Statistical Inference
Stat 111 is the sequel to Stat 110, turning probability into inference: estimators, maximum likelihood, confidence intervals, hypothesis testing, and Bayesian inference, taught with the same story-driven style. It's the second core course for statistics concentrators and a favorite of quant-leaning economics and CS students.
Fennie is independent and not affiliated with Harvard University. This is an unofficial study guide.
What makes it hard
Inference inverts the mental direction of Stat 110, so from model to data becomes from data back to model, and students fluent in probability still wobble at the conceptual layer: what a confidence interval does and doesn't say, what the likelihood actually is. The problems demand the same creative setup instincts as 110, now with statistical judgment stacked on top.
What you'll cover
- • Estimators and their properties
- • Maximum likelihood estimation
- • Confidence intervals
- • Hypothesis testing and p-values
- • Bayesian inference
- • Regression and prediction
The STAT 111 study guide
How to study for Harvard STAT 111, step by step.
- 1
Re-sharpen Stat 110 before the term starts
Stat 111 assumes the named distributions, conditioning instincts, and expectation tools of 110 are still warm. A one-week review of distribution stories and Bayes' rule pays off all semester.
- 2
Interrogate every interval and test verbally
Write in plain English what each confidence interval and p-value claims, and what it doesn't. The conceptual misstatements are exactly what exam questions are engineered to catch.
- 3
Work the likelihood from scratch each time
For every model you meet, write the likelihood, log it, and maximize it by hand at least once. The mechanical fluency frees attention for the judgment questions layered on top.
- 4
Compare Bayesian and frequentist answers side by side
Running both analyses on the same problem and explaining where they differ is the deepest comprehension check the course offers, and a recurring exam format.
Today
Today's STAT 111 plan
What a Fennie Daily Plan looks like for STAT 111. Yours is built from your own syllabus and adapts every day to your deadlines and progress.
First plan free, no card required. Fennie is independent and unaffiliated with your school.
FAQ
Is Stat 111 harder than Stat 110?
Different hard. The problem-solving creativity carries over, but inference adds a conceptual layer about what statistical statements mean. Students who only computed in 110 feel the difference.
Do I need Stat 110 before Stat 111?
Yes. 111 builds directly on 110's distributions, conditioning, and expectation toolkit. Taking them back to back keeps the probability fresh.
Is Stat 111 useful for data science?
Very. Estimation, testing, and Bayesian reasoning are the inferential core under every applied method. It pairs naturally with CS 109A's applied workflow.