University of Leeds

Exploratory Data Analysis

Taught in English


Gain insight into a topic and learn the fundamentals

Robert Aykroyd

Instructor: Robert Aykroyd

Intermediate level

Recommended experience

9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Prepare for a degree

What you'll learn

  • Explain the different data types and apply data preparation methods to clean data.

  • Explore ways to visualise data using the software R.

  • Understand how visualisation of data can inform statistical model selection.

Details to know


3 quizzes

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There are 3 modules in this course

This first week introduces you to data types (categorical, discrete, and continuous) and representing data via graphical summaries (or data visualisation). You will go through the steps you need to take to prepare data for analysis and data cleaning, by identifying missing data and outliers. You learn about and practice common graphical summaries such as box plots, histograms, and kernel density estimation (KDE).

What's included

5 videos6 readings2 quizzes1 ungraded lab

This second week gives you the opportunity to apply your knowledge of graphical summaries from Week 1 in greater depth, with tasks in RStudio to complete such as preparing data for analysis and data cleaning, by identifying missing data and outliers.

What's included

2 readings1 quiz1 discussion prompt1 ungraded lab

In this final week, you have the opportunity to build on your experiences of RStudio and data analysis using graphical summaries in Week 2. In Week 3, you complete a substantive task in RStudio to complete and there is a graded peer review where you share your output from the RStudio lab with a fellow student.

What's included

2 readings1 peer review1 ungraded lab


Robert Aykroyd
University of Leeds
2 Courses1,005 learners

Offered by

Recommended if you're interested in Data Analysis

Prepare for a degree

Taking this course by University of Leeds may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.

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