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

testVariable <- 1.9
# getting high level data type with class() and low level data type with typeof
cat(class(testVariable), typeof(testVariable)) 


cat(class(testVariable), typeof(testVariable))

## Explanation
The first task we were given was to find the **high-level** data type of the given `testVariable`. We can do this by using the `class()` function with the given `testVariable`. The second task was to print the **low-level** data type of the `testVariable` and for that, we use the `typeof()` function with the `testVariable`.

> A function is a set of instructions that perform a task. We will learn more about functions later in the course.

We pass both these functions to `cat()` for printing.






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

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

Solution Review: Variables

Solution: Use `class()` and `typeof()`

Explanation