This course aims to introduce learners to the R software, covering topics such as programming examples, statistical functions, data handling, strings, data management, basic calculations, functions, and matrices. By the end of the course, students will be able to use R for data analysis, visualization, and statistical computations. The teaching method includes hands-on examples, demonstrations, and practical exercises. This course is intended for individuals interested in learning R programming for data analysis and statistical purposes.
Overview
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.
Taught by
Ch 30 NIOS: Gyanamrit
