Statistics 20 - Introduction to Probability and Statistics

Statistics 20: Introduction to Probability and Statistics (Fall 2010, UC Berkeley). Taught by Professor Deborah Nolan, this course provides an introduction to probability and statistics. For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

01. Data, Let's Collect some 19. Probability: Hypothesis Testing
02. Intro to the R Project, Functions in R 20. Hypothesis Testing; Roulette Wheel
03. Distribution of Quantitative Variables 21. Boxes and Hypothesis Tests
04. Variables and Functions in R 22. Two Probability Laws and Hypothesis Tests for Averages
05. Lecture 23. Central Limit Theorem
06. BMI (Body Mass Index), Numerical Summaries of Quantitative Data 24. Hypothesis Tests for Averages
07. Graphic Composition Overview 25. Survey Design
08. Scatter Plots, Studying the Relationship between Two Quantitative Variables 26. Project Overview
09. Numerical Summaries of Data 27. Sampling
10. Fisher's "Lady Tasting Tea" Experiment 28. Featured Plots
11. Design of Experiments 29. More on Sampling
12. Design of Experiments (cont.) 30. Correlation and Regression
13. The Box Model 31. Fitting Lines to Data
14. Informal Analysis of an Experiment 32. Lecture
15. Probability; Deck of Cards 33. More on Regression
16. Conditional Probability 34. Regression Concepts
17. Pascal' & Fermat's Solutions 35. Relationships between Categorical Variables
18. Probability Distributions, R & Probability