About this course
Looking for the best way to get started with data analysis using R? This is the course for you.
You’ll start with the basics—installing R, exploring RStudio, and loading your datasets—then progress to confidently summarizing, analyzing, and visualizing your data. Our bite-sized video lessons cover crucial topics like univariate descriptive statistics, exploring relationships between variables, and powerful chart-making with ggplot2. You’ll work with real-world scenarios and guided exercises that reinforce every concept.
We designed this course for learners at all levels—no prior programming or statistics background required. By the end, you’ll know how to seamlessly wrangle, analyze, and present your data with clarity and confidence. Start anytime and work at your own pace. You’re just a few clicks away from a brand-new data analysis skill set!
What you’ll learn
- Install and navigate R and RStudio, understanding key functionalities.
- Install essential packages for statistical analyses
- Import and clean data from Excel or CSV files into R for analysis.
- Summarize categorical data using frequency tables
- Calculate descriptive statistics (mean, median, standard deviation) for continuous data
- Exploring relationships between variables with crosstabulations, mean comparisons and correlations
- Developing different kinds of charts using the ggplot2 package
- Interpret and report summary statistics effectively for decision-making.
Course content
Introduction
- Welcome
- What is R and R Studio
Getting Started
- Installing R and RStudio
- The RStudio interface
- Getting started with R code and the RStudio interface
- Using R Scripts
- Installing and loading packages
- Getting help in RStudio
Working with data
- Setting the working directory
- Loading CSV files
- Loading Excel files
- Exploring the data and variables
- Accessing columns and rows
- Renaming columns
Descriptive statistics in R
- Types of data
- Creating frequency tables
- Summary statistics
- Comparing means across groups
- Crosstabulation
- Correlations
Charts
- Introduction to ggplot2
- Histograms
- Frequency bar charts
- Bivariate bar charts
- Clustered bar charts
- Scatter plots
Exporting and reporting
- Exporting your output
- Reporting frequencies
- Reporting summary statistics
- Reporting mean comparisons
- Reporting crosstabulations
- Reporting correlations
Transforming variables
- Introduction to variable transformation
- Ranking
- Binning
- Recoding
- Calculating new variables
Conclusion
- Conclusion and next steps
Instructor
Alexander Mtembenuzeni
Data Analyst, Instructor
DATAFORDEV Founder
Alexander has over 10 years experience training social impact organizations in data analytics. He also has consulted for small and big organizations alike - developing data collection tools, building M and E systems and analyzing data. He is a 4.6/5-rated instructor on Udemy.com where he has several courses with a combined over 7,000 students. He also loves blogging and creating tutorial videos for the Data for Development YouTube channel.
Frequently asked questions
Does this course offer a certificate?
Yes. You will automatically get a certificate of completion as soon as you complete the course and pass the graded quizzes and project
How long will it take for me to complete the course?
We recommend investing 2 hours of learning per day. With that time investment, you will finish the course including the hands-on practices in 14 days.
Which days and times does the course run?
This course is self paced. Once you enroll, you can go through the learning content at any time, and at your own pace!
Instant access
Start as soon as you enroll
Approximately 14 days to complete
Suggested 2 hours per day
Level
Beginner to intermediate
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