Course: Introductory Statistics - Online Course for Credit


  • 03 January 2014
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This course is the equivalent of a semester course in introductory statistics. Credit is available via the American Council on education's Credit Recommendation Service (see below). The course features the use of resampling and simulation techniques (picking numbers from a hat, throwing dice, etc.) that make probabilistic statistics more transparent and understandable. The goal is real understanding, not cookbook learning, and even the most anxious novice (as well as the expert!) will benefit. It was developed by Peter Bruce, President of the Institute for Statistics Education at; he has published a number of papers in the area of resampling and is the co-author of Data Mining for Business Intelligence (Wiley, 2010).

Aim of Course:

The course is comprised of two separate courses, taken together:

Part 1: Statistics 1 - Probability and Study Design (4 weeks)

Part 2: Statistics 2 - Inference and Association (4 weeks)

Course Program:

WEEK 1: Study Design, Statistical Significance

Intro, Study Design
Measures of Central Location and Variability
Data Format
Null Hypothesis
Normal Distribution

WEEK 2: Categorical Data, Contingency Tables

Categorical Data
Graphical Exploration
Simple Probability
Normal Distribution again
2-Way (Contingency) Tables
Conditional Probability

WEEK 3: More Probability, Random Sampling, The Bootstrap

Bayes Rule
Random Sampling

WEEK 4: Confidence Intervals

Point Estimates
Confidence Intervals
Formula Counterparts
Standard Error
Beyond Random Sampling

WEEK 5: Confidence Intervals for Proportions and Means

CI Proportion
CI Mean
CI Difference in Means
CI Difference in Proportions
Hypothesis Tests vrs. Confidence Intervals

WEEK 6: Tests for Two Means, Proportions; Paired Comparisons

Test 2 Means
Test 2 Proportions
Paired Comparisons
1-way and 2-way hypotheses

WEEK 7: Chi-Square, Directional Hypotheses

More than 2 Samples
Chi Square
Goodness of Fit
Null and Alternative Hypotheses
1-Way and 2-Way Hypotheses

WEEK 8: Simple Linear Regression

Simple Regression
Regression Inference

Please note this is an online course lasting until 7th March 2014.

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