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18.05 | Spring 2014 | Undergraduate

# Introduction to Probability and Statistics

Listed in the following table are assigned readings that students were expected to complete prior to attending class sessions. Students also completed online multiple choice or numerical answer questions based on each week’s readings. Students received instant feedback and could make multiple attempts. [Note: the online reading questions are not available to OpenCourseWare users.]

WEEK # | SES # | READINGS |
--- | --- | --- | ---
Probability
1 | C1 | 1a: Introduction (PDF) 1b: Counting and Sets (PDF) |
C2 | 2: Probability: Terminology and Examples (PDF) R Tutorial 1A: Basics R Tutorial 1B: Random Numbers |
2 | C3 | 3: Conditional Probability, Independence and Bayes’ Theorem (PDF) |
C4 | 4a: Discrete Random Variables (PDF) 4b: Discrete Random Variables: Expected Value (PDF) |
3 | C5 | 5a: Variance of Discrete Random Variables (PDF) 5b: Continuous Random Variables (PDF) 5c: Gallery of Continuous Random Variables (PDF) 5d: Manipulating Continuous Random Variables (PDF) |
4 | C6 | 6a: Expectation, Variance and Standard Deviation for Continuous Random Variables (PDF) 6b: Central Limit Theorem and the Law of Large Numbers (PDF) 6c: Appendix (PDF) |
C7 | 7a: Joint Distributions, Independence (PDF) 7b: Covariance and Correlation (PDF) |
5 | C8 | Class 8: Exam Review (PDF) Class 8: Exam Review Solutions (PDF) |
| C9 | No readings assigned |
Statistics: Bayesian Inference
5 | C10 | 10a: Introduction to Statistics (PDF) 10b: Maximum Likelihood Estimates (PDF) |
6 | C11 | 11: Bayesian Updating with Discrete Priors (PDF) |
C12 | 12a: Bayesian Updating: Probabilistic Prediction (PDF) 12b: Bayesian Updating: Odds (PDF) |
7 | C13 | 13a: Bayesian Updating with Continuous Priors (PDF) 13b: Notational Conventions (PDF) |
C14 | 14a: Beta Distributions (PDF) 14b: Bayesian Updating with Continuous Data (PDF) |
8 | C15 | 15a: Conjugate Priors: Beta and Normal (PDF) 15b: Choosing Priors (PDF) |
C16 | 16: Probability Intervals (PDF) |
Statistics: Frequentist Inference—Null Hypothesis Significance Testing (NHST)
9 | C17 | 17a: The Frequentist School of Statistics (PDF) 17b: Null Hypothesis Significance Testing I (PDF) |
C18 | 18: Null Hypothesis Significance Testing II (PDF) |
10 | C19 | 19: Null Hypothesis Significance Testing III (PDF) |
C20 | 20: Comparison of Frequentist and Bayesian Inference (PDF) |
11 | C21 | No readings assigned |
Statistics: Confidence Intervals; Regression
12 | C22 | 22: Confidence Intervals Based on Normal Data (PDF) |
C23 | 23a: Confidence Intervals: Three Views (PDF) 23b: Confidence Intervals for the Mean of Non-normal Data (PDF) |
13 | C24 | 24: Bootstrap Confidence Intervals (PDF) |
C25 | 25: Linear Regression (PDF) |
14 | C26 | No readings assigned |
C27 | No readings assigned |

## Course Info

##### Instructors

- Dr. Jeremy Orloff
- Jonathan Bloom

##### Departments

- Mathematics

##### As Taught In

Spring 2014

##### Level

Undergraduate

##### Topics

- Mathematics
  - Discrete Mathematics
  - Probability and Statistics

##### Learning Resource Types

assignment_turned_in Problem Sets with Solutions
grading Exams with Solutions
notes Lecture Notes
co_present Instructor Insights
theaters Other Video

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