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Statistical Application Development with R and Python - Second Edition

You're reading from  Statistical Application Development with R and Python - Second Edition

Product type Book
Published in Aug 2017
Publisher
ISBN-13 9781788621199
Pages 432 pages
Edition 2nd Edition
Languages
Toc

Table of Contents (19) Chapters close

Statistical Application Development with R and Python - Second Edition
Credits
About the Author
Acknowledgment
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Data Characteristics 2. Import/Export Data 3. Data Visualization 4. Exploratory Analysis 5. Statistical Inference 6. Linear Regression Analysis 7. Logistic Regression Model 8. Regression Models with Regularization 9. Classification and Regression Trees 10. CART and Beyond Index

Summary


The reader should now be clear with the distinct nature of variables that arise in different scenarios. In R, the reader should be able to verify that the data is in the correct format. Furthermore, the important families of random variables are introduced in this chapter, which should help the reader in dealing with them when they crop up in their experiments. Computation of simple probabilities were also introduced and explained.

In the next chapter, the reader will learn how to perform the basic R computations, creating data objects, and so on. As data can seldom be constructed completely in R, we need to import data from external foreign files. The methods explained help the reader to import data in file formats such as .csv and .xls. Similar to importing, it is also important to be able to export data/output to other software. Finally, the R session management will conclude the next chapter.

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Statistical Application Development with R and Python - Second Edition
Published in: Aug 2017 Publisher: ISBN-13: 9781788621199
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