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Learning To Program With R

Video Description

In this Learning R training course, expert author Stuart Greenlee 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. Stuart 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.

Table of Contents

  1. Introduction
    1. Introduction And Course Overview 00:01:40
    2. About The Author 00:00:36
    3. Installing R And R Studio 00:04:07
    4. Navigating R Studio 00:05:11
    5. Packages 00:03:40
    6. Assigning Variables 00:03:31
    7. Numbers, Strings, And Booleans 00:05:26
    8. Workspace Operations 00:07:59
    9. How To Access Your Working Files 00:01:15
  2. Basic Operations And Manipulations
    1. Basic Operators 00:04:36
    2. Vectors 00:07:26
    3. Sequences 00:04:45
    4. Basic Statistical Functions 00:06:27
    5. Matrices 00:06:51
    6. Matrix Operations 00:05:29
    7. Basic Matrix Statistics 00:04:12
    8. Generating Random Numbers 00:08:01
    9. String Functions 00:07:46
    10. Dates And Times 00:07:56
  3. Plotting
    1. Line Plots 00:08:20
    2. Plotting Arguments 00:04:31
    3. Bar Graphs And Histograms 00:06:49
    4. Scatter Plots 00:06:29
    5. Probability Plots 00:06:34
    6. Combining And Saving Plots 00:04:51
  4. Working With Data
    1. Arrays 00:04:11
    2. Lists 00:03:58
    3. Data Frames 00:05:35
    4. Data Import 00:05:34
    5. Missing Data - Part 1 00:03:56
    6. Missing Data - Part 2 00:04:10
    7. Ordering And Sorting 00:04:17
    8. Subsetting And Indexing 00:04:41
    9. Merging Data 00:04:21
    10. Examining Files And Objects 00:03:49
  5. Data Analysis
    1. Descriptive Statistics 00:05:50
    2. Apply Functions 00:03:38
    3. Linear Models 00:06:08
    4. Extracting Model Information 00:05:06
    5. Principal Componant Analysis 00:02:49
  6. Time Series Data
    1. XTS Objects 00:03:59
    2. ACF Plots 00:02:53
    3. Decomposition 00:02:43
    4. Exponential Smoothing 00:04:05
    5. Rolling Functions 00:04:26
    6. ARIMA Models 00:04:36
  7. Conditional Statements And Loops
    1. If Statements 00:05:59
    2. For Loops 00:04:24
    3. While Loops 00:03:02
    4. Appending Loops 00:04:01
  8. User-Defined Functions
    1. Writing Functions 00:04:37
    2. Debugging Functions 00:05:10
    3. Recursive Functions 00:02:07
  9. Saving Data
    1. Saving Different Types Of Data 00:02:02
    2. Additional Resources 00:02:00