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Last updated:

September 23, 2023

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

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.

Course Curriculum

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

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