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Exploratory Data Analysis in R

4.9+
19 reviews
Intermediate

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

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4 Hours15 Videos54 Exercises
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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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In the following Tracks

Certification Available

Data Analyst with R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track
  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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    Exploring categorical data
    50 xp
    Bar chart expectations
    50 xp
    Contingency table review
    100 xp
    Dropping levels
    100 xp
    Side-by-side bar charts
    100 xp
    Bar chart interpretation
    50 xp
    Counts vs. proportions
    50 xp
    Conditional proportions
    50 xp
    Counts vs. proportions (2)
    100 xp
    Distribution of one variable
    50 xp
    Marginal bar chart
    100 xp
    Conditional bar chart
    100 xp
    Improve pie chart
    100 xp
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Certification Available

Data Analyst with R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track

Datasets

Cars dataComics dataImmigration dataRaw life expectancy dataNames dataRaw U.S. income data

Collaborators

Collaborator's avatar
Nick Carchedi
Collaborator's avatar
Tom Jeon
Andrew Bray HeadshotAndrew 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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Don’t just take our word for it

*4.9
from 19 reviews
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  • Jorge E.
    11 months

    10/10

  • Youngkee J.
    about 1 year

    Thank you!

  • Martina B.
    about 1 year

    I really like the way the instructor structures the knowledge and skill, he wanted us to acquire and also the fact, that we actually had to think for ourselves.

  • Nicolas F.
    about 1 year

    This course was so practical and helpful - it gave excellent strategies on how to explore your data and understand its structure! Well done, all.

  • Oladapo A.
    over 1 year

    Am rating it five, because it cost me nothing, but, in my fair review, the course wasn't as simplified as her sisters courses, proved quite challenging to understand its concept especially its application.

"10/10"

Jorge E.

"Thank you!"

Youngkee J.

"I really like the way the instructor structures the knowledge and skill, he wanted us to acquire and also the fact, that we actually had to think for ourselves."

Martina B.

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