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

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


Homepage

https://www.udemy.com/course/programming-with-r/