R programming for data analysis | tutorials for beginners #rprogramming

R programming for data analysis. Section 1. Getting started working with R programming. Lecture 1.Outline for tutorials What are the tutorials all about? R - one of the most popular programming languages and framework for statistical computing and data science Objective - to bring you up to start this comprehensive software as quickly as possible, such that you can apply it effectively to your own data. Who these tutorials are for? Anyone who tries to start programming in R at his/her first time Anyone may have heard but not programmed at all before Anyone who have used other programming/statistical packages in your working, and want to learn to use R for your data analysis as quickly as possible. Basic knowledge of using your computer is a prerequisite. What these tutorials cover? Section 1- installation of R and RStudio, set up R working environment, etc. Section 2 - R data structure, import and create data objects. Section 3 - Basic data management methods: type conversions, recoding variables, dates, missing values, selecting and dropping variables, sorting, merging, sub-setting, etc. Section 4 - Advanced data management methods: mathematical and statistical functions, functions for string and character, control flow, write your own functions, and reshaping and aggregating datasets, basic descriptive statistics. Section 5 - R graphics: Using ggplot2 package for plotting. Section 6 – Using Dplyr package for data management. Data, Code, Exercises Combines PPT and real working in Rstudio. Built-in dataset in R framework Code source file for each lecture Many thanks and hope you will enjoy the course of Beginning using R for data analysis ! #rprogramming #outline #tutorial #rdatacode