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Data explorations
Information and Meaning
Quantitative epsitemology
Tutorial: Getting started
Discussion questions
The value of openness
Tutorial: Repositories and version control
Discussion questions
Exercise 1: Github & Jupyter
What is a theory?
Discussion questions
Models as testable hypotheses
Tutorial: Introduction to R, functions, and good coding habits
Discussion questions
Exercise 2: Coding Habits & Functions
Data as objects and architectures
Tutorial: Data as Objects and Tidy Data
Discussion questions
Exercise 3: Data objects
Techniques for data cleansing
Tutorial: Data Cleansing and the Tidyverse
Discussion questions
Exercise 4: Data cleansing
Visualization as analysis
Tutorial: Basics of plotting
Discussion questions
Exercise 5: Using ggplot
Visualization through human eyes
Tutorial: More advanced plotting
Discussion questions
Exercise 6: More plotting options
Knowledge
The bias-variance tradeoff
Discussion questions
Linear models
Tutorial: Refresher on working with matrices
Discussion questions
Exercise 7: Linear models
The ordinary least squares solution
Tutorial: Refresher for solving oridinary least squares
Discussion questions
Exercise 8: Linear models, continued
Limits and variations of linear regression
Tutorial: More on linear models
Discussion questions
Classifiers
Tutorial: Basics classifiers
Discussion questions
Exercise 9: Classification
Mixed effects models
Tutorial: Running linear mixed effects models
Discussion questions
Exercise 10: Mixed effects
The beauty of kNN
Tutorial: Running kNN models
Discussion questions
Exercise 11: The beauty of kNN
Cross validation
Tutorial: Implementing cross validation
Discussion questions
Exercise 12: Cross validation
Resampling methods
Tutorial: Boostrap and permutation tests
Discussion questions
Exercise 13: Resampling methods
Mediation and moderation
Tutorial: Running mediation and moderation models
Discussion questions
Exercise 14: Mediation
Power analysis via simulations
Tutorial: Running basic power analyses
Discussion questions
Exercise 15: Power analyses
Selecting the best model
Tutorial: Model selection
Discussion questions
Exercise 16: Model selection
Regularized regression
Tutorial: Basic ridge and LASSO models
Discussion questions
Exercise 17: Regularized regression
Principal component methods
Tutorial: Basic PCA approaches
Discussion questions
Exercise 18: Principal component methods
Understanding
Reconsidering the p-value
Discussion questions
Bayes factor
Tutorial: Estimating Bayes factors
Discussion questions
Errors and inferences
Discussion questions
Telling your data story
Discussion questions
Theories as social constructs
Discussion questions
Index
