R & Stata For Beginners: Data Analysis And Visualization

Learn R & Stata from scratch: install, manage, analyze, and visualize data with examples and step-by-step guides.

What you'll learn

Students will learn to use Stata and R for data analytics

Students will learn data manipulation using R and Stata

Students will learn and understand how to deal with a wide variety of data types

Students will be able to interpret the analysis output

Students will learn plotting with R and Stata

Requirements

No programming experience is required. Having a functioning Stata software is essential. R is a free software.

Description

In this comprehensive course, you’ll gain hands-on experience with both R and Stata, learning everything you need to start analyzing and visualizing data with confidence.You’ll start from the very beginning, installation and setup, and progress through all the essential skills, including:Core programming concepts: objects, operators, logical expressions, functions, factorsData structures: vectors, lists, matrices, and data framesData handling: importing, saving, and inspecting datasets; creating variables; transformations; subsetting dataPractical utilities: managing working directories, clearing memory, installing packagesData wrangling: handling missing values, conditional calculations, proportionsAnalysis & visualization: summary statistics, single-variable and multi-variable plotsSpecial topics: basics of date handling, comparing matrices vs lists vs vectorsThis course is suited for both beginners and professionals. You can learn Stata and R from the inside out in one course, complete with downloadable videos and resource files.About the instructor:The course is taught by Dr. Fahad, who holds a PhD in Business and Management from Warwick Business School and an MPhil from the University of Cambridge. With years of experience teaching data analysis to undergraduates and postgraduates, he understands where students struggle most and has designed this course to make learning clear, structured, and approachable. If you need more information, please get in touch!

Overview

Section 1: Data Handling & Visualization in R

Lecture 1 Installing R and R Studio

Lecture 2 Objects in R, Vectors and Shortcut Keys

Lecture 3 Saving in R: Codes (.R) and workspace (.RData)

Lecture 4 Operators in R: Variables, Logicals and Operations

Lecture 5 Functions in R: In-built and Custom Functions

Lecture 6 Factors in R: Reference Levels and the 'relevel()' Function

Lecture 7 Vector vs Matrices vs Lists in R

Lecture 8 Data Frames in R

Lecture 9 Dates in R

Lecture 10 Packages in R

Lecture 11 Loading Data in R

Lecture 12 Variables, Transformations and Group Calculations in R

Lecture 13 Subsetting in R

Lecture 14 Managing Objects and Workspace in R: Saving and Clearing

Lecture 15 Summary Functions in R

Lecture 16 Missing Values in R: Detection and Calculations

Lecture 17 Conditions and Proportions in R

Lecture 18 Single Variable Plots in R

Lecture 19 Multiple Variable Plots in R

Lecture 20 Plot Syntax in R

Section 2: Data Handling & Visualization in Stata

Lecture 21 Integers and Operators in Stata

Lecture 22 Managing Packages in Stata

Lecture 23 Managing Variables in Stata: 'gen' and 'egen'

Lecture 24 Vectors and Matrices in Stata

Lecture 25 Time and Date in Stata

Lecture 26 Managing Data in Stata: Loading, Saving and Replacing

Lecture 27 Managing Variables in Stata

Lecture 28 Subset Data in Stata

Lecture 29 Removing, Saving and Keeping in Stata

Lecture 30 Summarize, Return, and Linear Relationship in Stata

Lecture 31 Missing Values in Stata

Lecture 32 Conditions and Proportions in Stata

Lecture 33 Single Variable Plots in Stata

Lecture 34 Multiple Variable Plots in Stata

This course is for researchers and beginners alike, who want to familiarize themselves with R and Stata.