Random Variables and Simulations
7
Models
Statistical Computing
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Introduction
R Programming
1
Basic R Programming
2
Control Flow
3
Functional Programming
4
Scripting and Piping in R
5
Further Resources
Random Variables and Simulations
6
Random Variables
7
Models
8
Random Number Generator
9
Monte Carlo Methods
10
Markov Chain Monte Carlo Methods
Randomizations
11
Permutation Tests
12
Permutation Regression
Monte Carlo Methods
13
Monte Carlo Integration
14
Monte Carlo Hypothesis Testing
15
Monte Carlo Optimization
16
Monte Carlo Methods Case Study 1
17
Monte Carlo Methods Case Study 2
18
Monte Carlo Methods Case Study 3
Bootstrapping
19
Parametric Bootrapping
20
Nonparametric Boostrapping
Data Manipulation, Summarization, and Graphics
21
Importing Data
22
Data Manipulation
23
Data Summarization
24
Graphics
Reporting Data
25
Quarto Documents
26
Presentations
Table of contents
7.1
Bernoulli Model
7.1.1
Distribution Functions
7.1.2
Expected Value
7.1.3
Variance
7.2
Binomial Model
7.2.1
Distribution Functions
7.2.2
Expected Value
7.2.3
Variance
7.3
Poisson Model
7.3.1
Distribution Functions
7.3.2
Expected Value
7.3.3
Variance
7.4
Negative Binomial Model
7.4.1
Distribution Functions
7.4.2
Expected Value
7.4.3
Variance
7.5
Multinomial Model
7.5.1
Distribution Functions
7.5.2
Expected Value
7.5.3
Variance
7.6
Uniform Model
7.6.1
Distribution Functions
7.6.2
Expected Value
7.6.3
Variance
7.7
Normal Model
7.7.1
Distribution Functions
7.7.2
Expected Value
7.7.3
Variance
7.8
Gamma Model
7.8.1
Distribution Functions
7.8.2
Expected Value
7.8.3
Variance
7.9
Beta Model
7.9.1
Distribution Functions
7.9.2
Expected Value
7.9.3
Variance
7.10
Weibull Model
7.10.1
Distribution Functions
7.10.2
Expected Value
7.10.3
Variance
Random Variables and Simulations
7
Models
7
Models
7.1
Bernoulli Model
7.1.1
Distribution Functions
7.1.2
Expected Value
7.1.3
Variance
7.2
Binomial Model
7.2.1
Distribution Functions
7.2.2
Expected Value
7.2.3
Variance
7.3
Poisson Model
7.3.1
Distribution Functions
7.3.2
Expected Value
7.3.3
Variance
7.4
Negative Binomial Model
7.4.1
Distribution Functions
7.4.2
Expected Value
7.4.3
Variance
7.5
Multinomial Model
7.5.1
Distribution Functions
7.5.2
Expected Value
7.5.3
Variance
7.6
Uniform Model
7.6.1
Distribution Functions
7.6.2
Expected Value
7.6.3
Variance
7.7
Normal Model
7.7.1
Distribution Functions
7.7.2
Expected Value
7.7.3
Variance
7.8
Gamma Model
7.8.1
Distribution Functions
7.8.2
Expected Value
7.8.3
Variance
7.9
Beta Model
7.9.1
Distribution Functions
7.9.2
Expected Value
7.9.3
Variance
7.10
Weibull Model
7.10.1
Distribution Functions
7.10.2
Expected Value
7.10.3
Variance
6
Random Variables
8
Random Number Generator