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.
In this chapter, you will learn how to create graphical and numerical summaries of two categorical variables.
In this chapter, you will learn how to graphically summarize numerical data.
Now that we've looked at exploring categorical and numerical data, you'll learn some useful statistics for describing distributions of data.
Apply what you've learned to explore and summarize a real world dataset in this case study of email spam.
PrerequisitesIntroduction to Data in R
Assistant Professor of Statistics at Reed College
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Devon Edwards Joseph
Lloyds Banking Group
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Harvard Business School
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Decision Science Analytics, USAA