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Statistics for Behavioral Science

Statistics for Behavioral Science (NYU Open Education). Instructor: Professor Elizabeth Bauer. This course provides students with the basic tools for evaluating data from studies in the behavioral sciences, particularly psychology. Students will gain familiarity with data description, variance and variability, significance tests, confidence intervals, correlation and linear regression, analysis of variance, and other related topics. The goal is to learn the application of statistical reasoning to decision making. Current events are often used to illustrate these issues.

Lecture 01 - Intro to Psych Statistics
Lecture 02 - Frequency Tables, Graphs, and Distributions
Lecture 03 - Measures of Central Tendency and Variability Part 1
Lecture 04 - Measures of Central Tendency and Variability Part 2
Lecture 05 - Standardized Scores and Normal Distribution Part 1
Lecture 06 - Standardized Scores and Normal Distribution Part 2
Lecture 07 - Intro to Hypothesis Testing; One Group Z - Test
Lecture 08 - Interval Test and the T - Distribution
Lecture 09 - T - Test for Two Independent Sample Means
Lecture 10 - Statistical Power and Effect Size Part 1
Lecture 11 - Statistical Power and Effect Size Part 2
Lecture 12 - Linear Correlation
Lecture 13 - Linear Regression Part 1
Lecture 14 - Linear Regression Part 2
Lecture 15 - Matched T-Test
Lecture 16 - One-Way Independent ANOVA
Lecture 17 - Multiple Comparisons
Lecture 18 - Linear Contrasts
Lecture 19 - Two-Way ANOVA
Lecture 20 - Interactions
Lecture 21 - Repeated Measures ANOVA Part 1
Lecture 22 - Repeated Measures ANOVA Part 2
Lecture 23 - Chi-Square