Gain the R programming language fundamentals for doing the applied
statistics useful for data exploration and analysis in data science
and data mining. This book covers topics ranging from R syntax
basics, descriptive statistics, and data visualizations to
inferential statistics and regressions. After learning R's syntax,
you will work through data visualizations such as histograms and
boxplot charting, descriptive statistics, and inferential
statistics such as t-test, chi-square test, ANOVA, non-parametric
test, and linear regressions. Learn R for Applied Statistics is a
timely skills-migration book that equips you with the R programming
fundamentals and introduces you to applied statistics for data
explorations. What You Will Learn Discover R, statistics, data
science, data mining, and big data Master the fundamentals of R
programming, including variables and arithmetic, vectors, lists,
data frames, conditional statements, loops, and functions Work with
descriptive statistics Create data visualizations, including bar
charts, line charts, scatter plots, boxplots, histograms, and
scatterplots Use inferential statistics including t-tests,
chi-square tests, ANOVA, non-parametric tests, linear regressions,
and multiple linear regressions Who This Book Is For Those who are
interested in data science, in particular data exploration using
applied statistics, and the use of R programming for data
visualizations.
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