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

# Problem Statement
Implement a function `evenOdd` that takes a `vector` of numbers as input and returns a `vector` where each element of the output vector has the string "even" or "odd" depending on the corresponding element of the input `vector`.


## Input
A `testVariable` containing the `vector` to be tested.

## Output
A `vector` where each element is either "even" or "odd" depending on the state of the corresponding element of the input `testVariable` vector.

## Sample Input
```
testVariable <- c(78, 100, 2)
```

## Sample Output
```
"even" "even" "even"
```
## Test Yourself
Write your code in the given area. If you get stuck, you can look at the solution.

Let's test your ability to return data from a function.

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

Exercise 13: Returning from a Function

Problem Statement