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OpenPSYC
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What is Open Science?
01 - Success in Learning Statistics
02 - Research methods and terminology
02-A Investigating the World Around Us
02-B Key terms and definitions of probability and statistics
02-C Random and non-random sampling
02-D Nominal, ordinal, interval, ratio
02-D Discrete and Continuous Variables
03 - Charts
03-A Raw Frequency Tables
03-A Grouped Frequency Tables
03-B Bar Graphs
03-B Histograms and Frequency Polygons
03-B Cumulative Lines and Stem and Leaf Plots
04 - Central tendency
04-A What are the Mean, Median, and Mode
04-B Central Tendency and Skew
05 - Variability
05-A Measures of Variation
06 - Standard distributions and z-scores
06-A Standard Distributions and Z-scores
07 - Correlation
07-A Defining and visualizing correlation
07-B Pearson's r
07-C Multiple Correlations
07-D Spearman's Rho
07-E Correlation Assumptions
08 -Regression
08-A Line of Best Fit
08-B Coefficient of determination
08-C Simple Regression
08-D Multiple Regression
08-E Assumptions of Regression
09 - Probability
09-A Probability Distributions
09-B Introduction to Probability
09-C Probability Rules
09-D Independence and Mutual Excuslivity
09-E Bayesian Probability
10 -Normal and binormal distribution probabilities
10-A Continuous Random Variable Distribution
10-B Normal distribution introduction
10-C Computing probabilities of the normal distribution
10-D Discrete distributions and probability density functions
10-E Compute binomial distributions
10-F Distinguishing between different distributions
11- NHST
11-A The logic and hypotheses of NHST
11-B Type I and Type II error
11-C The steps of NHST
12 - NHST with binomial
12-A Hypothesis test for a population proportion
12-B Experimental designs
How to run a binomIal test
Nonparametric methods
13 - Sampling distributions
13-A Introduction to sampling distributions
13-B Introduction to the central limit theorem
13-C Central limit theorem for sample means
Standard error of the mean
14 - NHST with normal distribution
14-A NHST for sample means of a continuous random variable with p-values
14-B NHST for sample means of a continuous random variable with critical...
14-C Cohen's d
14-D NHST with the normal approximation for the binomial distribution
14-E Assumptions of normal distribution
15 - Statistical Power
15-A Defining and visualizing power
15-B Factors impacting power
15-C Computing power
16 - NHST and Open Sci
16-A The p-value
16-B Bayesian alternatives
16-C What is open science?
16-C Why open science?
17 - NHST with one sample t-test
17-A Introduction to t distribution
17-C NHST with t-distribution
17-D Normal versus t distribution
17-E: NHST with Correlation
17-E: NHST with Correlation
17-F: One Sample t-test assumptions
18 - Confidence Intervals
18-A Confidence interval introduction
18-B Computing confidence intervals with normal distribution
18-C Computing confidence intervals with the t distribution
18-D Computing confidence intervals with the binomial distribution
18-E Interpreting confidence intervals
19 - NHST with independent samples t-test
19-A Independent samples t statistic
19-B Independent samples with pooled variance
19-C Independent samples t-test with pooled variance example
19-D Cohen’s d for Independent Samples t-test
19-E Independent samples t-test assumptions
20 - NHST with dependent samples t-test
20-A Dependent samples t-test
20-B Cohen's d for independent samples t-test
20-C1 Assumptions of dependent t-test
20-C Assumption of dependent t-test
21 - NHST with one way ANOVA
21-A Introduction to Analysis of Variance (ANOVA)
21-C ANOVA hypotheses
21-D ANOVA f-statistic
21-E ANOVA f-distribution
21-F ANOVA table
22 - Bayesian Information Criterion
Information for instructors: Homework sets
Tables
OpenPSYC
Introduction to Analysis of Variance (ANOVA)
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