
Home 

Welcome to the learnr.org interactive R tutorial with Examples and Exercises.
If you want to learn R for statistics, data science or business analytics, either you are new to programming or an experienced programmer this tutorial will help you to learn the R Programming language fast and efficient.
R is a programming language used extensively for statistics and statistical computing, data science and business analytics. There are different libraries in R which are used for statistics and graphical techniques for simple stats tests, linear and time series modeling, classification, clustering, regression analysis and many more.
If you are an absolute beginner in R and want to learn R for data analysis or data science from R experts I will strongly suggest you to see this R for Absolute Beginners Course
The field of data science is exploding these days and R and Python are the two languages mainly used for data analytics techniques due to their syntax, ease of use and application. R has many libraries for statistical computing and data analysis. If you learn R programming you can expect a salary starting from $75k while the average salary is $120k in data science jobs in USA. Data analysts and data scientists are in demand and there are a number of opportunities if one knows the skill. For current salaries and recent openings you may google it yourself.
R is opensource which means anyone and everyone can use it without paying. It is free under GNU license. Most of R packages are also available as free and you can use them for noncommercial as well as commercial activities. Statistical and analysis softwares usually cost from a few hundred to thousands of dollar, R provides the same functionality free of cost. If you have some extra bucks you may try costly softwares though.
R runs equally well on all platforms windows, linux or mac. Hence you may have a linux environment at office, windows at home and mac laptop for travelling, you will have the same experience at all platforms. The software development environment is same and also the applications run seamlessly at all platforms.
R is ranked as number 5 in most popular programming languages by IEEE. It shows the interest in R is increasing and the fields of analytics, data science, machine learning and deep learning are exploding.
The effectiveness and application of R programming is illustrated by the fact that many tech giants are using it. Companies like Google, Microsoft, Twitter, Ford etc are using R. This explains the concreteness and robustness of R.
Usually it is said that the learning curve of R is steep. Well, individuals with some programming experience may learn it without any hurdle. People without any programming background can also learn it with ease with a complete learning schedule and learning it step by step. Remember Rome was not built in a day. You can not expect to learn R in one sitting or a day or a few days. Regular practice of R coding and understanding the logic and philosophy are the key to success in learning R.
In this tutorial each R topic is divided into segments starting from a simple concept and then building on that knowledge moving towards complex ideas. The method to learn R is divide and conquer. Learn one topic at a time and get a good grasp over the concept and logic and write some R programs about the topic you are learning. Also try to solve the challenges given at the end of each tutorial. In this way you will learn this language fast and will set a solid foundation which will help you at advanced stages of data analysis.
Good enough introduction of R. There is no time to waste! lets start first concept of R programming right now. We provide R tutorial for total beginners even those who have never used any programming language before. So we start from the idea of variables.
The first idea to learn in every programming language is the concept of variables. Variables are like boxes or containers which store a value or some data. In a programming language we have to use numbers, characters, words etc but before using them we have to store them in some box or container so that we may use them later. Every variable has a name and some type, usually called as data type. In C, C++ or Java one has to tell the data type of variable, however in R you don't have to worry about it. Simply give a name to variable and thats it. Lets suppose we want to store or save age of a person in R. We give the name age to variable that will store the number in it. In R the code will be
> age < 25
Here the first greater than sign > indicates the R prompt. We write code after that.
< or arrow is assignment operator in R. It assigns the value at its right to the variable at its left. Here it is assigning 25 to variable age or simply it is storing 25 number in age variable or box.
And now if you want to print this variable use the print function like this.
> print(age)
[1] 25
Wow, you have succeeded in assigning a value to a variable, storing some value in box and then later used that value in a function from that box. print function simply prints the value of any variable on R console.
This is easy, isn't it? if you follow this site, you will be able to learn R in the same simple and easy way, step by step & Fast.