Statistics 21 - Introductory Probability and Statistics for Business

Statistics 21: Introductory Probability and Statistics for Business (Fall 2009, UC Berkeley). Statistics 21 is a service course designed primarily for Business students. It is not very mathematical, but you need to be comfortable with math at the level of high-school algebra. Taught by Professor Philip B. Stark, this course covers topics: reasoning and fallacies, descriptive statistics, association, correlation, regression, elements of probability, set theory, propositional logic, chance variability, random variables, expectation, standard error, sampling, hypothesis tests, confidence intervals, experiments and observational studies, as well as common techniques of presenting data in misleading ways.


Lecture 01 - Introduction, Reasoning and Fallacies
Lecture 02 - Reasoning and Fallacies
Lecture 03 - Data: Types of Data, Displaying Data, Measures of Location
Lecture 04 - Measures of spread or variability, Multivariate Data and Scatterplots
Lecture 05 - Association, Correlation, Computing the Correlation Coefficient
Lecture 06 - Regression, Regression Diagnostics
Lecture 07 - Errors in Regression, Counting, Permutations
Lecture 08 - Combinations, Card Hands
Lecture 09 - Probability: Philosophy and Mathematical Background
Lecture 10 - Review
Lecture 11 - Set Theory: The Language of Probability
Lecture 12 - Probability: Axioms and Fundaments
Lecture 13 - Propositional Logic
Lecture 14 - The "Let's Make a Deal" (Monty Hall) Problem
Lecture 15 - Probability Meets Data
Lecture 16 - Random Variables and Discrete Distributions
Lecture 17 - The Long Run and the Expected Value
Lecture 18 - Standard Error
Lecture 19 - The Norman Approximation, Markov's and Chebyshev's Inequalities for Random Variables
Lecture 20 - Sampling
Lecture 21 - Estimating Parameters from Simple Random Samples
Lecture 22 - Confidence Intervals
Lecture 23 - Hypothesis Testing: Does Chance Explain the Results?
Lecture 24 - Does Treatment Have and Effect?
Lecture 25 - Review

SticiGui: Statistics Tools for Internet and Classroom
Philip B. Stark, Department of Statistics, University of California, Berkeley. Statistics means never having to say you're certain.