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R Curriculum: 5 Chapters, 38 Lessons — pelatihan.org
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Curriculum
R Curriculum
Learn R online with 38 structured lessons, code examples, and 190 quiz questions.
38 lessons
5 chapters
190 questions
Summaries and key points are free to preview. Full lessons, code examples, and quizzes require a subscription.
01
R Tutorial
16 lessons
01
R HOME
This R-language tutorial homepage presents a key gateway for anyone who wants to learn statistical computing and data analysis. R is an open source programming language and…
02
R Intro
This lesson examines the history and competitive advantage of R in the era of big data. R was originally developed by Ross Ihaka and Robert Gentleman at the University of…
03
R Get Started
This lesson guides the installation of the R interpreter from CRAN and the use of the R interactive interface. Developers are taught how to run commands directly on the R console…
04
R Syntax
This lesson reviews the rules of code syntax in R. In R, the statement is executed line by line and does not require a semicolon at the end of the line, although semicolon can be…
05
R Comments
This lesson explains how to write comments on R program using the tag character (#). The commentary serves to provide documentation of the record and will not be processed by the…
06
R Variables
This lesson reviews the creation of variables and rules for identifier naming in R. Variables are used to store data in memory for statistical manipulation. Developers will study…
07
R Data Types
This lesson reviews the basic data types in R. The data in R is divided into numeric (decimal), integer (integer), complex (imaginary number), character (text), and raw (raw…
08
R Numbers
This lesson deals with three types of numbers in R: numeric, integer, and complex. R provides a conversion function between numeric types such as as.numeric() and as.integer().…
09
R Math
This lesson reviews the very rich mathematical functions inherent in R. Starting with basic operations like square roots, absolute values, displacement, to trigonometry and…
10
R Strings
This lesson discusses the manipulation of text (String/Character) in R. In R, the string is flanked by a double or single quotation. Developers will learn basic text processing…
11
R Booleans
This lesson is a peek at the logical data type (Boolean) in R. The logical value in R is represented by TRUE (or abbreviated T) and FALSE (or abbreviated F). The developer will…
12
R Operators
This lesson reviews the various operators groups in R. R distinguishes the arithmetic operator (+, -, *, /, ^, %%, %/%), the comparison operator (==,!=, <, >), as well as the…
13
R If...Else
This lesson discusses the branching sequence with the constructions 'if', 'else if', and 'else' in R. Developers were also introduced to the popular built-in vector function…
14
R While Loop
This lesson reviews the 'while' repetition in R that executes the block of code repeatedly during the evaluation condition of the value TRUE. The developer will learn how to set…
15
R For Loop
This lesson discusses the repetition of 'for' in R that is used to iterate the entire element within a vector, array, or list. The repetition for in R has a declarative syntax…
16
R Functions
This lesson reviews the creation of custom functions in R using the keyword 'function'. The function helps to wrap up the logic of the analysis that can be reused. The developer…
02
R Statistics
5 lessons
01
R Statistics Intro
This lesson leads the developer to the foundation of descriptive statistical computing in R. Descriptive analysis aims to summarize the important features of a data set without…
02
R Data Set
This lesson introduces a set of built-in datasets that are ready to be used for training in R without the need to import external files. The standard 'datasets' package includes…
03
R Max and Min
This lesson discusses the search for the lowest and highest extreme values in a dataset using the functions min(), max(), which are often used in preprocessing statistical data.…
04
R Mean Median Mode
This study reviews three of the most fundamental measures of data centralization (Measures of Central Tendency): Mean (arithmetic mean), Median (middle value), and mode (most…
05
R Percentiles
This study reviews the percentiles and quartiles in the analysis of the distribution of statistical data in R. The percentage divides the data into a hundred equal parts, while…
03
R Data Structures
7 lessons
01
R Data Structures
This lesson provides a comprehensive overview of the main data structure in R. Understanding the structure of data is very important because all statistical analysis is built on…
02
R Vectors
This lesson is going into the vector, which is the most basic data structure in R. All the single scalar data in R is actually a one-dimensional vector. Developers will learn the…
03
R Lists
This study reviews List data structures in R that are capable of accommodating a variety of heterogeneous data types and objects. In one list, you can store numbers, strings,…
04
R Matrices
This study reviews the data structure of the Matrix in R which is a collection of two-dimensional elements lined and columned with homogeneous data types. Matrix is created using…
05
R Arrays
This lesson discusses Arrays in R which are multi-dimensional homogeneous data structures (more than 2 dimensions). The array is created by calling the function array() and…
06
R Data Frames
This lesson paints a Data Frame which is the most fundamental data structure and is often used in data analysis in R. Data frames present data in the form of two-dimensional…
07
R Factors
This lesson discusses Factors in R that are specifically designed to handle categorical data. The categorical variables have a finite set of values called 'levels'. Factors are…
04
R Graphics
5 lessons
01
R Plot
This lesson reviews the basic graphical function plot() in R to visualize data into a point or line diagram. The plot() function is a generic function that adjusts visualization…
02
R Line
This lesson reviews the creation of line graphs to analyze trends and time series data. Developers are taught how to create a single line graph with plot(..., type="l"), add…
03
R Scatterplot
This study reviews the Scatterplot (scatter diagram) used to study the relationship or correlation between two continuous quantitative variables. Developers will learn how to…
04
R Pie Charts
This lesson discusses the creation of a pie chart in R using the function pie(). A circular diagram is used to show the percentage proportion of complementary categories to the…
05
R Bars
This lesson reviews the bar chart in R using the barplot() function. A bar diagram is very effective for comparing the magnitude of values between different categories.…
05
R Examples
5 lessons
01
R Examples
This lesson compiles a series of integrated code and scenario examples in R. Developers were asked to look at how the various components of the R language interact: from reading…
02
R Compiler
This lesson reviews the environment of execution and byte-code compilation in R. Although historically R was a purely interpreted language, modern R systems include a built-in…
03
R Practice Problems
This lesson provides a practical practice of solving statistical problems and manipulating dataset in R. The reader is tested to apply a combination of column selection, missing…
04
R Syllabus
This lesson outlines the complete syllabus and roadmap for learning the R programming language. It ranges from basic syntax and primitive data structures, to techniques for…
05
R Study Plan
This lesson presents a study plan aimed at mastering R from zero to ready-to-work. The steps are divided into the basic programming mastery phase, data analysis (EDA)…