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9:03
Difference Equations in R Part 2: Deterministic Chaos and Bifurcation Diagrams
9:53
Difference Equations in R Part 1: Representing Basic Population Dynamics
9:31
Differential Equations in R Part 2: Solving Lotka-Volterra Predation Equations
15:00
Differential Equations in R Part 1: Representing Basic Dynamics
11:41
Stochastic Models in R Part 1: Generating Random Numbers
13:51
Chi-squared Tests (Goodness of Fit) in R Part 1: Theory
11:48
Randomized Block Designs in R Part 1: Theory
7:48
Randomized Block Designs in R Part 2: Practice
11:26
Polynomial Regression in R Part 1: Theory
9:22
Polynomial Regression in R Part 2: Practice
9:50
One-way ANOVA Theory Part 1: Variance
8:17
One-way ANOVA Theory Part 3: Assumptions
10:56
One-way ANOVA Theory Part 2: ANOVA Basics
8:07
One-way ANOVA: Practice in R
11:13
Multiple Regression in R Part 1: Theory
9:13
Multiple Regression in R Part 2: Practice
14:58
Logistic Regression in R Part 1: Theory
10:03
Logistic Regression in R Part 2: Practice
11:24
Linear Regression Part 1: Theory
8:01
Linear Regression Part 2: Practice in R
13:52
Chi-squared Tests (Goodness of Fit) in R Part 2: Practice
12:21
Factorial ANOVA in R Part 1: Theory
8:18
Factorial ANOVA in R Part 2: Practice
12:07
Analysis of Covariance in R Part 1: Theory
8:47
Analysis of Covariance in R Part 2: Practice
10:04
The paste() Function in R
4:29
The apply Family of Functions in R Part 3: tapply()
6:33
The apply Family of Functions in R Part 2: lapply() and sapply()
11:53
The apply Family of Functions in R Part 1: apply()
7:42
The aggregate() Function in R
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