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R Programming By Example

You're reading from   R Programming By Example Practical, hands-on projects to help you get started with R

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788292542
Length 470 pages
Edition 1st Edition
Languages
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Authors (2):
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Omar Trejo Navarro Omar Trejo Navarro
Author Profile Icon Omar Trejo Navarro
Omar Trejo Navarro
Omar Trejo Navarro Omar Trejo Navarro
Author Profile Icon Omar Trejo Navarro
Omar Trejo Navarro
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Toc

Table of Contents (12) Chapters Close

Preface 1. Introduction to R 2. Understanding Votes with Descriptive Statistics FREE CHAPTER 3. Predicting Votes with Linear Models 4. Simulating Sales Data and Working with Databases 5. Communicating Sales with Visualizations 6. Understanding Reviews with Text Analysis 7. Developing Automatic Presentations 8. Object-Oriented System to Track Cryptocurrencies 9. Implementing an Efficient Simple Moving Average 10. Adding Interactivity with Dashboards 11. Required Packages

Graphing disaggregated data with boxplots

Creating bar graphs is useful when presenting results to people who are not familiar with statistics, but the fact that bar graphs aggregate information (just as we did in the bar graphs for top performers) means that, in reality, we lose information due to the reduction. If you're working with people who understand what quartiles are, then boxplots may be a useful visualization. They are an easy way to see individual distributions for different levels of a variable.

Each box represents the first quartile at the bottom, the third quartile at the top, and the median on the line in the middle. The lines that extend vertically reach up to any observation within 1.5 * IQR, where the interquartile range (IQR) is the distance between the first and third quartiles. Any observation beyond 1.5 * IQR is treated as an outlier and is shown individually...

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