Statistical Analysis with R

The digital world we live in has given companies and people access to staggering amounts of data, and anyone who can make use of that to drive valuable insights stands to benefit. The ability to work with large amounts of data is becoming a standard requirement for countless jobs across multiple industries.

R, probably the most well-known language for data analysis, has been used for years due to its robust statistical functionality, outstanding graphing ability, and extensibility through packages.

This interactive module will get us up to speed with R and assumes no prior knowledge of it. We'll start with the very basics and work our way up to advanced concepts like exception handling. By the time we're done, we'll be able to write detailed, useful code in R.

Learn R from Scratch

# What are Nested Functions?
A function is a set of statements that are executed together to achieve a specific goal or task.

In such a situation, we might have to use another function in the current function. This is called **nested functions**. We will be learning about **user-defined functions** being used in another **user-defined** function.

## Syntax of a Nested Function
```r
functionName1 <- function(argument1, argument2, ..., argumentN) 
{
  # Statements
}

functionName2 <- function(argument1, argument2, ..., argumentN) 
{
  # Statements
  functionName1(argument1, argument2, ..., argumentN)
}
```

Let's take an example of finding the **maximum** and **minimum** number in a `vector` using multiple functions.

We are going to learn all about nested functions in this lesson.

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

Nested Functions

What are Nested Functions?

Syntax of a Nested Function