Exploratory Data Analysis in R
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
- 4 hours
- 15 Videos
- 54 Exercises
- 53,309 Participants
- 3,950 XP
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Course Description
When your dataset is represented as a table or a database, it's difficult to observe much about it beyond its size and the types of variables it contains. In this course, you'll learn how to use graphical and numerical techniques to begin uncovering the structure of your data. Which variables suggest interesting relationships? Which observations are unusual? By the end of the course, you'll be able to answer these questions and more, while generating graphics that are both insightful and beautiful.
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1
Exploring Categorical Data
FreeIn this chapter, you will learn how to create graphical and numerical summaries of two categorical variables.
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Numerical Summaries
Now that we've looked at exploring categorical and numerical data, you'll learn some useful statistics for describing distributions of data.
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Exploring Numerical Data
In this chapter, you will learn how to graphically summarize numerical data.
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Case Study
Apply what you've learned to explore and summarize a real world dataset in this case study of email spam.
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1
Exploring Categorical Data
FreeIn this chapter, you will learn how to create graphical and numerical summaries of two categorical variables.
-
Exploring Numerical Data
In this chapter, you will learn how to graphically summarize numerical data.
-
Numerical Summaries
Now that we've looked at exploring categorical and numerical data, you'll learn some useful statistics for describing distributions of data.
-
Case Study
Apply what you've learned to explore and summarize a real world dataset in this case study of email spam.
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Andrew Bray
Assistant Professor of Statistics at Reed College
Andrew Bray is an assistant professor of statistics at Reed College. His interests are in computing, differential privacy, environmental statistics, and statistics education. He is a co-author of the infer package for tidy statistical inference.
See MoreCollaborators
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Nick Carchedi
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Tom Jeon