Programming With R. Learn How To Program In R - Beginners

A Beginners Guide To Getting Started Programming In R.

What you'll learn
Learn How To Get Started Programming In R
Requirements
PC or Mac
Description
This Learning R training course from Infinite Skills will teach you how to use R, a programming language used for statistical computing and graphics. This course is designed for beginners that have no previous R programming experience. You will require a fundamental understanding of statistics to get the most out of this course. You will start by learning how to install and navigate R studio, then move into learning basic operations like statistical functions, matrix operations, and string functions. This course will show you how to plot, including scatter plots, probability plots, and plotting arguments. This video tutorial will cover working with data and data analysis, such as extracting model information, examining files and objects, and subsetting and indexing. You will also learn about conditional statements and user-defined functions, including how to write and de-bug functions. Finally, you will learn how to save different types of data. Once you have completed this computer based training course, you will be fully capable of using R for developing statistical software and data analysis tools. Working files are included, allowing you to follow along with the author throughout the lessons.

Overview

Section 1: Introduction

Lecture 1 Important - Download These First - Working Files

Lecture 2 0101 Introduction And Course Overview

Lecture 3 0103 Installing R And R Studio

Lecture 4 0104 Navigating R Studio

Lecture 5 0105 Packages

Lecture 6 0106 Assigning Variables

Lecture 7 0107 Numbers, Strings, And Booleans

Lecture 8 0108 Workspace Operations

Lecture 9 0109 How To Access Your Working Files

Section 2: Basic Operations And Manipulations

Lecture 10 0201 Basic Operators

Lecture 11 0202 Vectors

Lecture 12 0203 Sequences

Lecture 13 0204 Basic Statistical Functions

Lecture 14 0205 Matrices

Lecture 15 0206 Matrix Operations

Lecture 16 0207 Basic Matrix Statistics

Lecture 17 0208 Generating Random Numbers

Lecture 18 0209 String Functions

Lecture 19 0210 Dates And Times

Section 3: Plotting

Lecture 20 0301 Line Plots

Lecture 21 0302 Plotting Arguments

Lecture 22 0303 Bar Graphs And Histograms

Lecture 23 0304 Scatter Plots

Lecture 24 0305 Probability Plots

Lecture 25 0306 Combining And Saving Plots

Section 4: Working With Data

Lecture 26 0401 Arrays

Lecture 27 0402 Lists

Lecture 28 0403 Data Frames

Lecture 29 0404 Data Import

Lecture 30 0405 Missing Data - Part 1

Lecture 31 0406 Missing Data - Part 2

Lecture 32 0407 Ordering And Sorting

Lecture 33 0408 Subsetting And Indexing

Lecture 34 0409 Merging Data

Lecture 35 0410 Examining Files And Objects

Section 5: Data Analysis

Lecture 36 0501 Descriptive Statistics

Lecture 37 0502 Apply Functions

Lecture 38 0503 Linear Models

Lecture 39 0504 Extracting Model Information

Lecture 40 0505 Principal Componant Analysis

Section 6: Time Series Data

Lecture 41 0601 XTS Objects

Lecture 42 0602 ACF Plots

Lecture 43 0603 Decomposition

Lecture 44 0604 Exponential Smoothing

Lecture 45 0605 Rolling Functions

Lecture 46 0606 ARIMA Models

Section 7: Conditional Statements And Loops

Lecture 47 0701 If Statements

Lecture 48 0702 For Loops

Lecture 49 0703 While Loops

Lecture 50 0704 Appending Loops

Section 8: User-Defined Functions

Lecture 51 0801 Writing Functions

Lecture 52 0802 Debugging Functions

Lecture 53 0803 Recursive Functions

Section 9: Saving Data

Lecture 54 0901 Saving Different Types Of Data

Lecture 55 0902 Additional Resources

Beginners To R Programming