Exploratory Data Analysis in R

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
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Clock4 HoursPlay15 VideosCode54 ExercisesGroup56,938 Learners
Database3950 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.

  1. 1

    Exploring Categorical Data

    Free
    In this chapter, you will learn how to create graphical and numerical summaries of two categorical variables.
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  2. 2

    Exploring Numerical Data

    In this chapter, you will learn how to graphically summarize numerical data.
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  3. 3

    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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  4. 4

    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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In the following tracks
Data Analyst Data ScientistStatisticianStatistics Fundamentals
Collaborators
Nick CarchediTom Jeon
Andrew Bray Headshot

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.
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Decision Science Analytics, USAA

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