Before we get started...-Before we get started - Introduction
Hi there
Welcome to Inferential Statistics!
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How to navigate this course
How to contribute
Before we get started...-Before we get started - What to expect from this course
General info - What will I learn in this course?
Course format - How is this course structured?
Requirements - What resources do I need?
Grading - How do I pass this course?
Team - Who created this course?
Honor Code - Integrity in this course
Useful literature and documents
Comparing two groups-Comparing two groups - Drawing inferences
Comparing two groups - Drawing inferences
1.01 Null hypothesis testing
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1.02 P-values
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1.03 Confidence intervals and two-sided tests
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1.04 Power
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Comparing two groups-Comparing two groups - Independent groups
Comparing two groups - Independent groups
1.05 Two independent proportions
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1.06 Two independent means
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Comparing two groups-Comparing two groups - Dependent groups
Comparing two groups - Dependent groups
1.07 Two dependent proportions
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1.08 Two dependent means
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Comparing two groups-Comparing two groups - Controlling for other variables
Comparing two groups - Controlling for other variables
1.09 Controlling for other variables
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Comparing two groups-Comparing two groups - Review
Comparing two groups - Transcripts
Categorical association-Categorical association - Chi-squared test for association
Categorical association - Chi-squared test for association
2.01 Categorical association and independence
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2.02 The Chi-squared test
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2.03 Interpreting the Chi-squared test
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Categorical association-Categorical association - Chi-squared test for goodness of fit
Categorical association - Chi-squared test for goodness of fit
2.04 Chi-squared as goodness-of-fit
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Categorical association-Categorical association - Sidenotes and an alternative to the Chi-squared test
Categorical association - Sidenotes and an alternative to the Chi-squared test
2.05 The Chi-squared test - sidenotes
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2.06 Fisher's exact test
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Categorical association-Categorical association - Review
Categorical association - Transcripts
Simple regression-Simple regression - Describing quantitative association
Simple regression - Describing quantitative association
3.01 The regression line
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3.02 The regression equation
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3.03 The regression model
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3.04 Predictive power
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Simple regression-Simple regression - Drawing inferences
Simple regression - Drawing inferences
3.05 Pitfalls in regression
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3.06 Testing the model
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3.07 Checking assumptions
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3.08 CI and PI for predicted values
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Simple regression-Simple regression - Exponential regression
Simple regression - Exponential regression
3.09 Exponential regression
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Simple regression-Simple regression - Review
Simple regression - Transcripts
Multiple regression-Multiple regression - Model
Multiple regression - Model
4.01 Regression model
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4.02 R and R-squared
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Multiple regression-Multiple regression - Tests
Multiple regression - Tests
4.03 Overall test
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4.04 Individual tests
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4.05 Checking assumptions
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Multiple regression-Multiple regression - Categorical predictors, categorical response variable and example
Multiple regression - Categorical predictors, categorical response variable and example
4.06 Categorical predictors
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4.07 Categorical response variable
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4.08 Interpreting results
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Multiple regression-Multiple regression - Review
Multiple regression - Transcripts
Analysis of variance-Analysis of variance - Basics and one-way ANOVA
Analysis of variance - Basics and one-way ANOVA
5.01 One-way ANOVA
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5.02 One-way ANOVA - Assumptions and F-test
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5.03 One-way ANOVA - Post-hoc t-tests
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Analysis of variance-Analysis of variance - Factorial ANOVA and regression
Analysis of variance - Factorial ANOVA and regression
5.04 Factorial ANOVA
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5.05 Factorial ANOVA - Assumptions and tests
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5.06 ANOVA and regression
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Analysis of variance-Analysis of variance - Review
Analysis of variance - Transcripts
Non-parametric tests-Non-parametric tests - The basics
Non-parametric tests - The basics
6.01 Non-parametric tests - Why and when
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6.02 The sign test
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Non-parametric tests-Non-parametric tests - Comparing groups with respect to mean rank
Non-parametric tests - Comparing groups with respect to mean rank
6.03 One sample - Wilcoxon signed rank test
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6.04 Two samples - Wilcoxon/Mann-Whitney test
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6.05 Several samples - Kruskal-Wallis test
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a note about test-names
Non-parametric tests-Non-parametric tests - Rank-based correlation & randomness
Non-parametric tests - Rank-based correlation & randomness
6.06 Spearman correlation
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6.07 The runs test
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Non-parametric tests-Non-parametric tests - Review
Non-parametric tests - Transcripts