Introduction to R Programming Language

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Free Download Introduction to R Programming Language
by Mohsen Nady
English | 2022 | ISBN: 177469039X | 449 pages | True PDF | 61.24 MB

This book covers some introductory steps in using R programming language as a data science tool. The data science field has evolved so much recently with incredible quantities of generated data. To extract value from those data, one needs to be trained in the proper data science skills like statistical analysis, data cleaning, data visualization, and machine learning. R is now considered the centerpiece language for doing all these data science skills because it has many useful packages that not only can perform all the previous skills, but also, has additional packages that was developed by different scientists in diverse fields. These fields include, but are not limited to, business, marketing, microbiology, social science, geography, genomics, environmental science, etc. Furthermore, R is free software and can run on all major Windows, Mac Os, and UNIX/Linux. The first two chapters involve installing and using R and RStudio. RStudio is an IDE (integrated development environment) that makes R easier to use and is more similar to SPSS or Stata. Chapters 3-8 covers the different R objects and how to manipulate them including the very popular one, dataframes. Chapter 9 is about importing different files into your R working session like text or excel files. Chapters 10 and 11 are dealing with different tidyverse packages that can do interesting summaries of different dataframes including different types of data visualizations. In the last chapter, it introduces how functions are created in R along with some control structures and useful functions. In all these chapters, many examples along with different codes and outputs are given to help your understanding of this powerful programming language. I hope this book will be great addition to your future data analysis projects.

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Introduction to R Programming
Published 4/2024
Duration: 10h28m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 9.51 GB​

Genre: eLearning | Language: English [/center]

Learn to Program in RStudio | Data Science | Packages | Functions | ggplot2

What you'll learn
Navigate the R statistical language and programming environment.
Identify RStudio functions and programming concepts.
Discover the packages and code needed to conduct fundamental mathematical, and statistical analysis in R.
Write code in R to solve sample problems.

Requirements
Having R and RStudio installed on your computer is recommended but not required. No programming or statistics experience is needed. You will learn everything you need to know.

Description
Welcome to Introduction to R Programming, named exactly the same as the university class I teach at Boise State University! I went through and filmed all of the lessons I created and had a ton of fun doing so! I imagine that the fun I had will translate to you also having fun throughout the course.
The course was originally designed to give students that had little to no programming or statistics experience the skills they needed to succeed in a future R Programming and/or statistics course. In these videos especially, I've included a lot of things that I've picked up in my professional usage of RStudio, so R Programmers of all skill levels will learn something new!
It is highly recommended that you install the R language and RStudio so that you can follow along with the lessons. A quick Google search for RStudio should help you get the R language and RStudio up and running. I uploaded all of the scripts I use in the videos so you can follow along with me. Since it's in video format, you can also take it at whatever pace you desire. I've also uploaded all of the assignment files along with their answer keys so you can check your work.
I'm excited to put my knowledge and creativity out there to help those who'd like to learn a new skill! I hope you have fun!
Who this course is for:
Social scientists not familiar with R Programming
Current or future statistics students where R is used for the class.

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