Introduction to R Software

Learn the fundamentals of R programming in this comprehensive 16-hour course. Explore data handling, statistical functions, and visualization techniques. Master vector indexing, list management, and matrix operations. Dive into conditional executions, loops, and logical operators. Practice with real-world examples and gain hands-on experience in data importing, sorting, and formatting. Discover R's powerful built-in functions and learn to create custom functions. Utilize R Studio and command-line interfaces for efficient coding. By the end of the course, develop proficiency in R for data analysis, statistical computing, and graphical representation.

Syllabus

Examples of Programming (CH_30).
Bivariate and Three dimensional plots (CH_30).
Statistical Functions - Boxplots, Skewness and Kurtosis (CH_30).
Data Handling - Importing Data Files from Other software (CH_30).
Statistical Functions : Frequency and Partition values (CH_30).
Statistical Functions : Graphics and Plots (CH_30).
Statistical Functions - Central Tendency and Variation (CH_30).
Examples of More Programming.
Strings -Display and Formating, Paste function.
Strings - Display and Formatting , Print and Format with Concatenate.
Strings - Display and Formatting , Print and Format Functions.
Data Management - Factors (continued).
Data Management - (Factors).
Vector Indexing (continued).
Data Management - Vector Indexing.
Data Management - Lists (continued).
Data Management - Lists.
Data Management - Sorting and Ordering.
Data Management Repeats.
Data Management Sequences.
Data Management Sequences.
Basic Calculations : Conditional executions and loops.
Basic Calculations : Truth table and conditional executions.
Basic Calculations : Logical Operators.
Basic calculations : Missing data and logical operators.
Basic calculations : Matrix Operations.
Functions and Matrices.
R as calculator, Built in functions and Assignment.
Basics of calculations , Basics and R as a calculator.
Introduction command line, Data Editor and R studio.
Introduction Help demo examples packages libraries.
Why R and installation procedure.