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Are you new to R?
Do you want to learn more about statistical programming?
Are you in a quantitative field?
You just started learning R but you struggle with all the free but unorganized material available elsewhere?
Do you want to hack the learning curve and stay ahead of your competition?
If your answer is YES to some of those points  read on!
This Tutorial is the first step  your Level 1  to R mastery.
All the important aspects of statistical programming ranging from handling different data types to loops and functions, even graphs are covered.
While planing this course I used the Pareto 80/20 principle. I filtered for the most useful items in the R language which will give you a quick and efficient learning experience.
Learning R will help you conduct your projects. On the long run it is an invaluable skill which will enhance your career.
Your journey will start with the theoretical background of object and data types. You will then learn how to handle the most common types of objects in R. Much emphasis is put on loops in R since this is a crucial part of statistical programming. It is also shown how the apply family of functions can be used for looping.
In the graphics section you will learn how to create and tailor your graphs. As an example we will create boxplots, histograms and piecharts. Since the graphs interface is quite the same for all types of graphs, this will give you a solid foundation.
With the R Commander you will also learn about an alternative to RStudio. Especially for classic hypthesis tests the R Coomander GUI can save you some time.
You can download the code pdf of every section to try the presented code on your own.
This tutorial is your first step to benefit from this open source software.
What R you waiting for?
Martin
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Section 1: Introduction  the very Basics of R  

Lecture 1 
R Level 1 Intro
Preview

02:57  
Lecture 2 
Download R and RStudio
Preview

04:22  
Lecture 3 
RStudio Orientation
Preview

18:26  
Lecture 4 
The Structure of the R Ecosystem
Preview

14:33  
Lecture 5 
R Help Features
Preview

17:49  
Lecture 6 
R Basics Script
Preview

Article  
Lecture 7 
Using the R Functions
Preview

11:01  
Lecture 8 
R Exercises
Preview

02:39  
Lecture 9 
Three Common Mistakes of R Beginners
Preview

11:03  
Lecture 10 
Your first Lines of R
Preview

14:38  
Lecture 11 
Using some basic Functions
Preview

12:59  
Lecture 12 
Exercise and Solutions  Basic Coding
Preview

06:16  
Lecture 13 
R Datasets and Dataframes
Preview

09:26  
Lecture 14 
Basic Graphs in R 1
Preview

10:52  
Lecture 15 
Basic Graphs in R 2
Preview

15:41  
Lecture 16 
Exercise and Solutions  Basic Graphs
Preview

03:10  
Lecture 17 
Thoughts on Learning R
Preview

12:38  
Section 2: Theoretical background  
Lecture 18  05:23  
In this lecture you will learn about basic and logical operators in R. 

Lecture 19 
Operators script
Preview

1 page  
Lecture 20  10:36  
In this video you will learn about the different types of objects in R: Vectors (1 dimension, 1 data type) Matrices (2 dimensions, 1 data type) Arrays (x dimensions, 1 data type) Data frames (2 dimensions, x data types) Lists (1 dimension, x data types) 

Lecture 21 
Object types script
Preview

2 pages  
Lecture 22  05:44  
In this video you will learn how to use mode/typof to identify data types in a vector. 

Lecture 23  4 pages  
Data Types script 

Lecture 24  06:00  
In this lecture you will learn how to create random numbers in three different distributions: Normal distribution Poison distribution Uniform distribution 

Lecture 25  01:10  
Take a few minutes to go through this exercise and see if you understood the lecture. 

Lecture 26  04:19  
Presentation of the solution 

Lecture 27 
Random number generation script

4 pages  
Lecture 28  06:48  
In this video you will learn how to import and export csv files from/to R. CSV (comma seperated values) is the best way to interact with Excel. 

Lecture 29 
Data export/import script

2 pages  
Section 3: Creating objects  
Lecture 30  06:36  
In this video you will learn: basics about matrices rows  columns creating diagonal matrices extracting a vector out of a matrix transposing 

Lecture 31  04:46  
In this video you will learn: getting the inverse of a matrix matrix multiplication crossproducts solving equation systems summary 

Lecture 32  00:37  
You can find the solution skript at the bottom of the matrices skript 

Lecture 33  01:18  
Presentation of the solution 

Lecture 34 
Matrices script

5 pages  
Lecture 35  07:10  
In this video you will learn about: definition of a list how to create a list naming lists elements of a list length of lists extracting elements out of a list combining lists mode of a list 

Lecture 36  01:40  
Take a few minutes to go through the exercises. At the end of the video you will see the solution. 

Lecture 37 
Lists script

3 pages  
Lecture 38  04:58  
In this video you will learn: basics about data frames structure of data frames creating data frames adding vectors to data frames attach function handling and extracting subsets of data frames 

Lecture 39  05:12  
In this video you will learn: extracting columns, rows and specific values out of a data frame filtering according to specific criteria and logical operations summary 

Lecture 40  02:28  
In this video you will learn how you can use factors to handle character vectors. 

Lecture 41  03:44  
Take a few minutes to solve this exercises. At the end of this video I will present the solution. 

Lecture 42 
Data frames script

6 pages  
Lecture 43 
Factors script

1 page  
Section 4: Functions in R  
Lecture 44  03:48  
In this video you will get a general idea about functions in R. You will learn about the syntax. 

Lecture 45  02:35  
In this video you will learn how you can use ... to create open ended functions. 

Lecture 46  06:47  
In this video you will learn about the ifelse statement. You will also see a summary about the functions section. 

Lecture 47  07:12  
Try to solve the exercises in this video. At the end of the video you will find the solution. 

Lecture 48 
Functions script

8 pages  
Section 5: Loops  
Lecture 49  06:27  
In this video you will get a general introduction about loops in R. I am also discussing the If statement. 

Lecture 50  06:01  
In this video you will learn about the For loop 

Lecture 51  04:29  
In this video you will learn about the While loop 

Lecture 52  06:11  
In this video you will learn about the repeat loop. You will also see a brief summary about what we learned on loops in R. 

Lecture 53  06:13  
Please take the time to solve the exercises I prepared for you in this video. At the end you will also find the solutions to it. 

Lecture 54  03:36  
This exercise is a bit harder. Try to calculate the prime numbers by using loops. 

Lecture 55 
Loop script

12 pages  
Section 6: Apply family  
Lecture 56  05:19  
In this video you will learn: general introduction to the apply family apply function 

Lecture 57  06:45  
In this lecture about the apply family of funxtions you will learn: tapply function by function 

Lecture 58  04:53  
In this video you will learn about the following functions of the apply family: eapply lapply sapply 

Lecture 59  06:22  
In this video you will learn about the following functions of the apply family: vapply replicate mapply 

Lecture 60  08:22  
In this video you will learn more about rapply and you will also get a summary of the apply functions. 

Lecture 61  03:35  
Take the time to solve this exercises I prepared for you. In the next video I will present the solution. 

Lecture 62  05:35  
In this video I am presenting the solutions to the apply exercises 

Lecture 63 
Apply family script

11 pages  
Section 7: Graphs in R  
Lecture 64  02:28  
In this section you will learn more about graphs in R. 

Lecture 65  04:26  
This is a brief introduction to the graphical parameters in R. 

Lecture 66  07:18  
In this video you learn how you can create boxplots: adding means to your boxplot adding different colours boxplot terminology 

Lecture 67  01:18  
In this video you will learn about the different ways in which you can export and store your graphs. 

Lecture 68  01:43  
Take your time to solve this boxplot exercise and test your knowledge. In the next video you will find the solution. 

Lecture 69  02:39  
Here you can find the solution to the boxplot exercise. 

Lecture 70  08:24  
In this video you will learn how to create pie charts in R: labelling pie charts pie charts with data frames 3D pie charts (using plotrix) Please note that you should download the library "plotrix" for this lesson 

Lecture 71  07:07  
In this video you will learn how to create histograms in R: modifying the bin count labelling modifying the axes frequency vs density adding curves to histograms 

Lecture 72  02:43  
Try to resemble the histogram I present to you in this video. At the end you will find the solution. 

Lecture 73  05:46  
In this video you will learn how you can put several datasets into one scatterplot. You will also learn about legends. 

Lecture 74  03:45  
Take a few minutes to solve this scatterplot exercise. At the end of the video you will find the solution. 

Lecture 75 
Graphs script

10 pages  
Section 8: Advanced topic: working with strings  
Lecture 76 
Working with Strings  Introduction

05:45  
Lecture 77 
Working with Strings  gsub

07:42  
Lecture 78 
Working with Strings  gsub advanced

05:23  
Lecture 79 
Regular Expressions Overview

2 pages  
Lecture 80 
Working with Strings  Library Stringr

05:10  
Lecture 81 
Exercise and Solution: Strings in R

03:46  
Lecture 82 
Code Section: Strings

Article  
Section 9: Using the R Commander GUI  
Lecture 83 
R Commander Intro

05:07  
Lecture 84 
Installation Hints

Article  
Lecture 85 
Getting Data into RCmdr

12:52  
Lecture 86 
Modeling with RCmdr

08:01 
RTutorials is your provider of choice when it comes to analytics training courses! Try it out – our 30,000+ students love it.
We focus on Data Science tutorials. Offering several R courses for every skill level, we are Udemy's number one R training provider. On top of that courses on Tableau, Excel and a Data Science career guide are available.
All of our courses contain exercises to give you the opportunity to try out the material on your own. You will also get downloadable script pdfs to recap the lessons.
The courses are taught by our main instructor Martin – trained biostatistician and enthusiastic data scientist / R user.
Should you have any questions, you are invited to check out our website, you can open a discussion in the course or you can simply drop us a pm.
We are there to help you boost your career with analytics training – Just learn and enjoy.