R Introduction: Part I

R Introduction: Part I

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1. Basic Syntax and Operations

In the initial section, you’ll dive into the foundational elements of R, such as generating output and performing elementary operations. This section will conclude with an exploration of the theory behind variables.

Basic Arithmetic

Using the print() Function

Integer Division and Remainders

Revenue Calculation

Assignment Operators

2. Basic Data Types and Vectors

You’ll become familiar with the vector class in R, which also handles individual values. Here, you’ll delve into the primary data types for singular values and learn how to manage multiple values of the same type simultaneously.

Type Conversion

Labeling Vectors

Indexing in Vectors

Modifying Vectors

Deleting Elements from Vectors

Arithmetic Operations with Vectors

3. Factors

Factors, also known as categorical variables, are prevalent in the real world. Examples include blood types, currencies, nationalities, and brands. Unlike numerical variables, factors have a limited set of possible values.

What is a Factor?

Indexing in Factors

Counting Values

Grouping Numeric Data

What is a Factor?

Factor variables are a fundamental concept in statistics and data analysis, often referred to as categorical variables. These variables differ from numerical variables in that they have a limited and fixed set of possible values. Examples of factor variables include blood type, currency, and nationality.

Conversely, variables such as monthly income, height, and price are typically not considered categorical due to their unlimited range of potential values. However, even these can be converted into categorical variables, a process we will explore in later chapters.

Before creating a factor variable, let's first create a vector of currencies:

In fact, a factor is a type of vector. To indicate to R that we are working with factor values, we use the factor() function and pass the relevant vector of values as an argument:

Upon execution, not only is the vector of values output, but we also see a line titled Levels:, which indicates all the distinct (unique) values the factor can take.

Task

Imagine we conducted a survey on blood groups and received 26 responses, which are now stored in the blood vector. Here's what you need to do:

Display the values of the original vector blood.
Convert blood into a factor and assign it to the variable blood_gr.
Display the values of blood_gr.

Everything was clear?

Section 3. Chapter 1

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Course Content

R Introduction: Part I

R Introduction: Part I

What is a Factor?

Factor variables are a fundamental concept in statistics and data analysis, often referred to as categorical variables. These variables differ from numerical variables in that they have a limited and fixed set of possible values. Examples of factor variables include blood type, currency, and nationality.

Conversely, variables such as monthly income, height, and price are typically not considered categorical due to their unlimited range of potential values. However, even these can be converted into categorical variables, a process we will explore in later chapters.

Before creating a factor variable, let's first create a vector of currencies:

In fact, a factor is a type of vector. To indicate to R that we are working with factor values, we use the factor() function and pass the relevant vector of values as an argument:

Upon execution, not only is the vector of values output, but we also see a line titled Levels:, which indicates all the distinct (unique) values the factor can take.

Task

Imagine we conducted a survey on blood groups and received 26 responses, which are now stored in the blood vector. Here's what you need to do:

Display the values of the original vector blood.
Convert blood into a factor and assign it to the variable blood_gr.
Display the values of blood_gr.

Everything was clear?

Section 3. Chapter 1

toggle bottom row

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