Introduction to Probability and Statistics | Mathematics | MIT OpenCourseWare

Course Info

Instructors

Departments

Mathematics

As Taught In

Spring 2014

Level

Undergraduate

Topics

Mathematics
- Discrete Mathematics
- Probability and Statistics

Learning Resource Types

Exam Solutions

Exams

Instructor Insights

Lecture Notes

Other Video

Problem Set Solutions

Problem Sets

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Lecture Notes

Class 1 Slides: Introduction, counting and sets

Class 1 Slides: Introduction, counting and sets

Slides for Class 1: Introduction, Counting and Sets

Class 2 Slides: Probability basics

Class 2 Slides: Probability basics

Reading for Class 2: Probability: Terminology and Examples

Class 3 Slides: Conditional probability, Bayes' theorem

Class 3 Slides: Conditional probability, Bayes' theorem

Class 4 Slides: Discrete random variables, expectation

Class 4 Slides: Discrete random variables, expectation

Class 5 Slides: Gallery of continuous variables, histograms

Class 5 Slides: Variance, continuous random variables

Class 5 Slides: Variance, continuous random variables

Class 5 Slides: Variance, continuous random variables

Class 6 Slides: Expectation, variance, law of large numbers and central limit theorem

Class 6 Slides: Expectation, variance, law of large numbers and central limit theorem

Class 7 Slides: Joint distributions: independence, covariance and correlation

Class 7 Slides: Joint distributions: independence, covariance and correlation

Class 8 Slides: Review for exam 1

Class 8 Slides: Review for exam 1

Class 10 Slides: Introduction to statistics; maximum likelihood estimates

Class 10 Slides: Introduction to statistics; maximum likelihood estimates

Class 11 Slides: Bayesian updating with known discrete priors

Class 11 Slides: Bayesian updating with known discrete priors

Class 12 Slides: Bayesian updating: probabilistic prediction; odds

Class 12 Slides: Bayesian updating: probabilistic prediction; odds

Class 13 Slides: Bayesian updating: continuous prior, discrete data

Class 13 Slides: Bayesian updating: continuous prior, discrete data

Class 14 Slides: Beta distributions: continuous data

Class 14 Slides: Beta distributions: continuous data

Class 15 Slides: Conjugate priors; choosing priors

Class 15 Slides: Conjugate priors; choosing priors

Class 16 Slides: Probability intervals

Class 16 Slides: Probability intervals

Class 17 Slides: Frequentist methods; NHST

Class 17 Slides: Frequentist methods; NHST

Class 18 Slides: NHST II: Significance level, power, t-tests

Class 18 Slides: NHST II: Significance level, power, t-tests

Class 19 Slides: NHST III: Gallery of tests

Class 19 Slides: NHST III: Gallery of tests

Class 20 Slides: Comparison of Bayesian and frequentist inference

Class 20 Slides: Comparison of Bayesian and frequentist inference

Class 21 Slides: Review for exam 2

Class 21 Solutions File: Review for exam 2

Class 22 Slides: Confidence intervals for normal data

Class 22 Slides: Confidence intervals for normal data

Class 23 Slides: Confidence intervals II

Class 23 Slides: Confidence intervals II

Class 24 Slides: Bootstrap confidence intervals

Class 24 Slides: Bootstrap confidence intervals

Class 25 Slides: Linear regression

Class 25 Slides: Linear regression

Class 26 Problems File: Review for final exam

Class 26 Slides: Review for final exam

Class 26 Solutions File: Review for final exam

Class 27 Problems File: Review for final exam, cont'd

Class 27 Problems: Review for final exam, cont'd

Class 27 Solutions File: Review for final exam, cont'd

Course Info

Instructors

Departments

Mathematics

As Taught In

Spring 2014

Level

Undergraduate

Topics

Mathematics
- Discrete Mathematics
- Probability and Statistics

Learning Resource Types

Exam Solutions

Exams

Instructor Insights

Lecture Notes

Other Video

Problem Set Solutions

Problem Sets

Browse Resources

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