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R & Stata for Beginners: Data Analysis and Visualization
Rating: 4.0 out of 5(1 rating)
1 students

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.
Created byDr. Fahad Mansoor Pasha
Last updated 8/2025
English
English

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

Course content

2 sections • 34 lectures • 2h 17m total length

  • Installing R and R Studio3:24

    Install R and R Studio. R Studio is one of the best IDEs (Integrated Desktop Environment) for R and Python.

  • Objects in R, Vectors and Shortcut Keys4:18

    Explore the 5 object types in R and the concept of vectors.

  • Saving in R: Codes (.R) and workspace (.RData)3:33

    Learn to save both the R script (codes) and all of your work environment (workspace).

  • Operators in R: Variables, Logicals and Operations5:33

    Learn the different operators in R. Operators are used for variable creations, math operations and logical conditions.

  • Functions in R: In-built and Custom Functions3:32

    R has a range of in-built functions that help with statistical and mathematical operations.

  • Factors in R: Reference Levels and the 'relevel()' Function2:37

    Factors are important when working with categories and dummy variables. We create factors and then alter them.

  • Vector vs Matrices vs Lists in R5:49

    Vectors and matrices are great for calculations. Vectors are 1-D, whereas matrices are 2-D. Lists are quite similar to vectors.

  • Data Frames in R2:25

    Learn how to create and query data frames.

  • Dates in R2:15

    Dates are vital to learn time series analysis. Learn the different date formats, including the ISO format.

  • Packages in R2:46

    Learn to install packages. You can copy and carry the packages to another computer!

  • Loading Data in R5:17

    Learn how to upload and manipulate datasets. You will practice on a '.csv' file.

  • Variables, Transformations and Group Calculations in R6:51

    Create variables, transform them and carry out group calculations. You can easily create variables using 'If-else' statements.

  • Subsetting in R6:06

    Learn to subset and order the data. You can subset the data for calculations and create new data frames.

  • Managing Objects and Workspace in R: Saving and Clearing2:37

    Learn to manage your workspace. You can view all objects in the workspace, remove objects and save them.

  • Summary Functions in R4:08

    Learn how to use in-built summary functions in R.

  • Missing Values in R: Detection and Calculations4:53

    Learn how to detect and do calculations with missing values.

  • Conditions and Proportions in R3:10

    You can carry out proportion calculations in R. In addition, you can specify conditions and do calculations, like conditional mean.

  • Single Variable Plots in R10:16

    Learn single variable plots, like Boxplots, Histograms, Kernel Plots, and QQ-plots.

  • Multiple Variable Plots in R4:41

    Learn plot elements that are useful for comparing multiple variables, like Lowess, Abline and Scatterplot matrices.

  • Plot Syntax in R3:57

    Learn details of plot elements in R. You can learn how to add titles, colors, legends, and lines. You can change line width, colors and much more!

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, factors

  • Data structures: vectors, lists, matrices, and data frames

  • Data handling: importing, saving, and inspecting datasets; creating variables; transformations; subsetting data

  • Practical utilities: managing working directories, clearing memory, installing packages

  • Data wrangling: handling missing values, conditional calculations, proportions

  • Analysis & visualization: summary statistics, single-variable and multi-variable plots

  • Special topics: basics of date handling, comparing matrices vs lists vs vectors

This 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!

Who this course is for:

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

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