1. Statistics for Psychology
A Quick Summary

2. Introduction Introduction to the Course The Nature of Statistics
Psychology and Science
Four parts and four steps
There are no neutral statistics
Variables, Summation Sign, Probability
Theory and Hypothesis
Testing with empirical observations
A self-correcting feedback loop in combination with healthy skepticism

3. Descriptive Statistics
Visual Presentations & Shape
Frequency tables and graphs
The normal distribution
Central Tendency
Various measures & outfits
3 Characteristics of any statistic
Skewed data, Deviation scores
Variation
Various measures and logic of calculating the std r x
Relative Location
Raw score & standardized
Proportions under the normal curve
Correlation
Design vs. Statistic
Understanding correlations and scatterplots
Pearson r: Logic, calculation, r2, assumptions, causation issues
std =
 (x - mean)2 N

4. Inferential Statisticsx α 
Hypothesis Testing
Types of hypotheses & falsification
The four part story
Hypothesis direction
Decisions vs. reality
What you want to test
What you want to say
What you need in order to generalize
What you need to reject the null
Inferential Statistical Tests
The four steps
Single sample, two sample tests, and Anova
Assumptions and logic for all
Detailed calculations for three
Decision tree for all
Reject
Fail to Reject
Null True
Null False I II + α -
Power