0.1 Esma6616.pdf
0.2 Syllabus
0.3 Assignments
0.4 Resma3.RData (Ver 3.2)
1.1 Installation and updating
1.2 R Markdown, HTML and Latex
1.3 R basics
1.4 Programming in R
1.5 List of base R commands
2.1 Identifying Students at Risk
2.2 A Simple Example
2.3 Notation, Formulas
3.1 Introduction
3.2 Conditional Probability and Independence
3.3 Random Variable, Distribution Function, Density and Random Vectors
3.4 Expectation
3.5 Inequalities and Limit Theorems
3.6 Transformations
3.7 Concepts of Statistics
4.1 Matrix and Vector Notation
4.2 Matrix Operations
4.3 Eigenvalues and Eigenvectors, Matrix Calculus
5.1 Expectation, Covariance and Correlation
5.2 Multivariate Normal Distribution
5.3 Sums of Squares, Mean and Variance of Quadratic Forms
5.4 Noncentral Chi-Square, F and t Distributions
5.5 Distribution and Independence of Linear and Quadratic Forms
6.1 Simple Linear Regression
6.2 Multiple Linear Regression
6.3 Geometric Interpretion, Centered Form
6.4 Normal Model and R2
6.5 Generalized Least Squares
6.6 Hypothesis Testing
6.7 Multiple Testing, Simultaneous Inference
6.8 Confidence and Prediction Intervals
6.9 Regression Diagnostics
6.10 Random Predictors
6.11 Bayesian Inference for Regression
7.1 Non-Full Rank Models
7.2 Estimation
7.3 Hypothesis Testing
7.4 One-Way ANOVA
7.5 Pairwise Comparisons
7.6 Power and Sample Size
7.7 Balanced Two-Way ANOVA
7.8 Unbalanced Two-Way ANOVA
8.1 ANCOVA
8.2 Generalized Least Squares
8.3 Linear Mixed Models
8.4 Nonlinear Regression
8.5 Logistic and Poisson Regression, Generalized Linear Models
8.6 Classification
8.7 Nonparametric Regression