You're reading from Hands-On Exploratory Data Analysis with R

Product typeBook

Published inMay 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789804379

Edition1st Edition

Languages

Tools

ggplot

Concepts

Data Analysis

Authors (2):

Radhika Datar

Harish Garg

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Probability plots

This section describes the creation of probability plots in R that can be used for didactic purposes and, predominantly, for the purpose of data analysis. The following functions are available for each distribution of probability plots in the format specified:

Name	Description
`dnorm()`	Density or probability function
`pnorm()`	Cumulative density function
`qnorm()`	Quantile function
`Rnorm()`	Random deviates

We will be creating probability plots for the bank dataset with reference to the age and balance parameters, which are regarded as the crucial parameters in establishing loan eligibility using the following steps:

Include the library within the R workspace. This is considered a mandatory step:

> library(ggplot2) 
Attaching package: 'ggplot2'
The following object is masked _by_ '.GlobalEnv':
mpg
Warning message...

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Hands-On Exploratory Data Analysis with R

Published in: May 2019Publisher: PacktISBN-13: 9781789804379

Authors (2)

Radhika Datar

Radhika Datar has more than 5 years' experience in software development and content writing. She is well versed in frameworks such as Python, PHP, and Java, and regularly provides training on them. She has been working with Educba and Eduonix as a training consultant since June 2016, while also working as a freelance academic writer in data science and data analytics. She obtained her master's degree from the Symbiosis Institute of Computer Studies and Research and her bachelor's degree from K. J. Somaiya College of Science and Commerce.
Read more about Radhika Datar

Harish Garg

Harish Garg is a Principal Software Developer, author, and co-founder of a software development and training company, Bignumworks. Harish has more than 19 years of experience in a wide variety of technologies, including blockchain, data science and enterprise software. During this time, he has worked for companies such as McAfee, Intel, etc.
Read more about Harish Garg

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