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Introduction
Graphing Distributions
Summarizing Distributions
Describing Bivariate Data
Probability
Research Design
Normal Distribution
Advanced Graphs
Sampling Distributions
Estimation
Logic of Hypothesis Testing

Tests of Means

Contents
Standard
Single Mean
Standard Video
t Distribution Demo
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Difference between 2 Means
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Robustness Simulation
Standard
Pairwise Comparisons
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Specific Comparisons
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Correlated Pairs
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Correlated t Simulation
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Comparisons (correlated)
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Pairwise (Correlated)
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Statistical Literacy
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Exercises
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Power
Regression
Analysis of Variance
Transformations
Chi Square
Distribution Free Tests
Effect Size
Case Studies
Calculators
Glossary

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Standard View

introduction | subliminal message exp example | significance test | calculating p with known sd | subliminal study conclusions | one-tailed vs two-tailed | calculations using z-scores | real world (estimating) | ADHD study t test | ADHD study conclusions | review of assumptions

Learning Objectives

Compute the probability of a sample mean being at least as high as a specified value when σ is known
Compute a two-tailed probability
Compute the probability of a sample mean being at least as high as a specified value when σ is estimated
State the assumptions required for item 3 above.

Audio by Alex Shabad