## Video description

R Programming for data science and data analysis. Apply R for statistics and data visualization with GGplot2 in R

**About This Video**

- Introductory guide to statistics - descriptive statistics and the fundamentals of inferential statistics
- Essentials of R-based programming - soar above the average data scientist and boost the productivity of your operations.
- Data manipulation and analysis techniques - learn to work with R's most comprehensive collection of tools and create meaning-heavy data visualizations and plots.

**In Detail**

R Programming is a skill you'll need if you want to work as a data analyst or a data scientist in your industry of choice. And why wouldn't you - data scientist is the hottest ranked profession in the US. But to do that, you need the tools and the skillset to handle data. R is one of the top languages to get you where you want to be. Combine that with statistical know-how, and you will be well on your way to your dream job. This course packs all of this, and more, in one easy-to-handle bundle, and it's the perfect start to your journey. So, welcome to R Programming for Statistics and Data Science, the course that will get you from a complete beginner in programming with R to a professional who can complete data manipulation on demand. It gives you the complete skillset to tackle any new data science project with confidence and critically assess your work and other people's.

Practicability is the key to this course, Using R, you have a wide variety of options where you can take the code provided within this course and expand on it in any number of directions. You'll reinforce your learning through numerous practical exercises.

## Publisher resources

## Table of contents

- Chapter 1 : Introduction
- Chapter 2 : Getting started
- Chapter 3 : The building blocks of R
- Chapter 4 : Vectors and vector operations
- Chapter 5 : Matrices
- Chapter 6 : Fundamentals of programming with R
- Chapter 7 : Data frames
- Chapter 8 : Manipulating data
- Chapter 9 : Visualizing data
- Chapter 10 : Exploratory data analysis
- Chapter 11 : Hypothesis Testing
- Chapter 12 : Linear Regression Analysis

## Product information

- Title: R Programming for Statistics and Data Science
- Author(s):
- Release date: October 2018
- Publisher(s): Packt Publishing
- ISBN: 9781789950298

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