This interactive R course covers everything from the basics, variables, and data types to advanced topics, such as recursion, file handling, and S3/S4 classes in R.

In today’s data-driven world, the ability to analyze large datasets is becoming a vital skill across industries. R, one of the most powerful languages for data analysis.
This interactive R course is designed for beginners, with no prior knowledge of R programming required. You will begin with fundamental concepts, such as R variables, data types in R, and basic functions like R print and R cat. As you progress, you will dive into more complex topics, including R vectors, lists, arrays, matrices, and data frames in R programming. You’ll also learn how to perform operations using arithmetic operators in R, relational operators in R, and logical operators in R. Further, the course covers advanced features like if statements in R, switch statements in R, loops in R, and recursion in R. 
Finally, you’ll gain hands-on experience with file handling in R, exception handling with try and except in R, and object-oriented programming using S3 and S4 classes in R.

Learn R

recursiveFibonacci <- function(testVariable) 
{
    if(testVariable <= 1) 
    {
        return(testVariable)
    } else 
    {
        return(recursiveFibonacci(testVariable - 1) + recursiveFibonacci(testVariable - 2))
    }
}

# Driver Code
recursiveFibonacci(0)
recursiveFibonacci(1)
recursiveFibonacci(2)
recursiveFibonacci(5)
recursiveFibonacci(6)

recursiveFibonacci <- function(testVariable) 
{
    if(testVariable <= 1) 
    {
        return(testVariable)
    } else 
    {
        return(recursiveFibonacci(testVariable - 1) + recursiveFibonacci(testVariable - 2))
    }
}

### Explanation
To find the element placed at the input index $n$ in the Fibonacci series we need the elements placed at $(n-1)$ and $(n-2)$ positions.

For example, if current index = $n$
then
```
fibonacciSeries[n] = fibonacciSeries[n-1] + fibonacciSeries[n-2].
```
This is a good situation where recursion can be used. 
Recursion means _function calling itself_, in the code above `recursiveFibonacci()` function calls itself with a lesser value several times. A termination condition is very important in recursion function: in this case, it is
```
if(testVariable <= 1) 
{
   return(testVariable)
}
```
so that the code returns directly for the lowest indexes.


## Explanation
To find the element placed at the input index $n$ in the Fibonacci series we need the elements placed at $(n-1)$ and $(n-2)$ positions.

For example, if current index = $n$
then
```
fibonacciSeries[n] = fibonacciSeries[n-1] + fibonacciSeries[n-2].
```
This is a good situation where recursion can be used. 
Recursion means _function calling itself_, in the code above `recursiveFibonacci()` function calls itself with a lesser value several times. A termination condition is very important in recursion function: in this case, it is
```
if(testVariable <= 1) 
{
   return(testVariable)
}
```
so that the code returns directly for the lowest indexes.


In this review, we give a detailed analysis of the solution to this problem.

Introduction to R

R variables

Data Structures in R

Operator in R

Conditional Statements in R

Loops in R

Function in R

Input/Output in R

Exception Handling in R

Classes in R

R Programming Challenges

Conclusion

Solution Review: Recursion

Solution: Recursion

Explanation