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

A **Factor** is an interesting data structure in R language used to categorize data. By categorizing data, we mean fields that take only predefined, a limited, or finite number of values **(categorical variables)**.


For example, the marital status of a person can be one of the following:
* Single
* Married
* Separated
* Divorced
* Widowed

Here we know that the possible values for marital status are $5$. These values are predefined and distinct and are called `levels`. 

## Creating Factors

Factors can be created using the `factor()` function. This function takes all the `levels` in the form of a **vector**. Let's dive right into the code.

A **Factor** is an interesting data structure in R language used to categorize data. By categorizing data, we mean fields that take only predefined, a limited, or finite number of values **(categorical variables)**.


For example, the marital status of a person can be one of the following:
* Single
* Married
* Separated
* Divorced
* Widowed

Here we know that the possible values for marital status are $5$. These values are predefined and distinct and are called `levels`. 

# Creating Factors

Factors can be created using the `factor()` function. This function takes all the `levels` in the form of a **vector**. Let's dive right into the code.

Here we are going to learn about R factors: how to create them and where they are used.

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

Factors