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Learn R Programming in 24 Hours - cover

Learn R Programming in 24 Hours

Alex Nordeen

Publisher: Publishdrive

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Summary

R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference.
 
R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple.
 
R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze.
 
Table of Contents
 
Chapter 1: What is R Programming Language? Introduction & Basics
 
Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows
 
Chapter 3: R Data Types, Arithmetic & Logical Operators with Example
 
Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice
 
Chapter 5: Factor in R: Categorical & Continuous Variables
 
Chapter 6: R Data Frame: Create, Append, Select, Subset
 
Chapter 7: List in R: Create, Select Elements with Example
 
Chapter 8: R Sort a Data Frame using Order()
 
Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread)
 
Chapter 10: Merge Data Frames in R: Full and Partial Match
 
Chapter 11: Functions in R Programming (with Example)
 
Chapter 12: IF, ELSE, ELSE IF Statement in R
 
Chapter 13: For Loop in R with Examples for List and Matrix
 
Chapter 14: While Loop in R with Example
 
Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples
 
Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files
 
Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm
 
Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File
 
Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example
 
Chapter 20: R Aggregate Function: Summarise & Group_by() Example
 
Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example
 
Chapter 22: Scatter Plot in R using ggplot2 (with Example)
 
Chapter 23: How to make Boxplot in R (with EXAMPLE)
 
Chapter 24: Bar Chart & Histogram in R (with Example)
 
Chapter 25: T Test in R: One Sample and Paired (with Example)
 
Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples)
 
Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example]
 
Chapter 28: Decision Tree in R with Example
 
Chapter 29: R Random Forest Tutorial with Example
 
Chapter 30: Generalized Linear Model (GLM) in R with Example
 
Chapter 31: K-means Clustering in R with Example
 
Chapter 32: R Vs Python: What's the Difference?
 
Chapter 33: SAS vs R: What's the Difference?
Available since: 10/31/2021.
Print length: 450 pages.

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