Simulation: Random Sampling

Course Content

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Installing R on a Mac

Installing R on a Mac

Installing R on Windows

Installing R on Windows

Writing Code: Setting Your Working Directory (Windows)

Writing Code: Setting Your Working Directory (Mac)

Overview and History of R

R Console Input and Evaluation

Data Types: R Objects and Attributes

Data Types: Vectors and Lists

Data Types: Matrices

Data Types: Factors

Data Types: Missing Values

Data Types: Data Frames

Data Types: Names Attribute

Data Types: Summary

Reading Tabular Data

Reading Large Tables

Textual Data Formats

Connections: Interfaces to the Outside World

Subsetting Basics

Subsetting Lists

Subsetting Matrices

Subsetting: Partial Matching

Subsetting: Removing Missing Values

Vectorized Operations

Control Structures: Introduction

Introduction to swirl

Control Structures: If-Else

Control Structures: For Loops

Control Structures: While Loops

Control Structures: Repeat, Next, Break

Your First R Function

Functions: Part 1

Functions: Part 2

Scoping Rules: Symbol Binding

Scoping Rules: R Scoping Rules

Scoping Rules: Optimization Example (OPTIONAL)

Coding Standards

Dates and Times

Loop Functions: lapply

Loop Functions: apply

Loop Functions: mapply

Loop Functions: tapply

Loop Functions: split

Debugging Tools: Diagnosing the Problem

Debugging Tools: Basic Tools

Debugging Tools: Basic Tools II

The str Function

Simulation: Generating Random Numbers

Simulation: Simulating a Linear Model

Simulation: Random Sampling

R Profiler: Part 1

R Profiler: Part 2

Final Exam - Mastering R Programming with Roger Peng

Mastering R Programming with Roger Peng

Understand the process of random sampling in R.

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