Book Name: Learn R for Applied Statistics
Author: Eric Goh Ming Hui
Year: 2019 
File size: 6.8 MB
File format: PDF
Learn R for Applied Statistics Pdf Book Description:
Profit the R programming language principles for doing the employed statistics useful for data mining and analysis from data science and information exploration. This publication covers subjects which range from R syntax principles, descriptive data, and information visualizations into inferential statistics and regressions. After studying R’s syntax, you may work through information visualizations including histograms and boxplot charting, descriptive statistics, and inferential data like t-test, chi-square test, ANOVA, non-parametric evaluation, and linear regressions.
Learn R Applied Statistics is a timely skills-migration publication that provides you with all the R programming principles and introduces one to applied data for information explorations. Discover R, data, data science, data mining, and large data. Master the principles of R programming, such as variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions. Utilize descriptive data. Create information visualizations, such as bar graphs, line graphs, scatter plots, boxplots, histograms, and scatterplots. Use inferential statistics such as t-tests, chi-square tests, ANOVA, non-parametric evaluations, linear regressions, and multiple linear regressions. People that are interested in data science, particularly data mining using applied statistics, and also the usage of R programming for information visualizations.