NPTEL : NOC:Introduction to R Software (Mathematics)

Co-ordinators : Prof. Shalabh


Lecture 1 - How to Learn and Follow the Course

Lecture 2 - Why R and Installation Procedure

Lecture 3 - Introduction _Help_ Demo examples_ packages_ libraries

Lecture 4 - Introduction _Command line_ Data editor _ Rstudio

Lecture 5 - Basics in Calculations

Lecture 6 - Basics of Calculations _ Calculator _Built in Functions Assignments

Lecture 7 - Basics of Calculations _Functions _Matrices

Lecture 8 - Basics Calculations: Matrix Operations

Lecture 9 - Basics Calculations: Matrix operations

Lecture 10 - Basics Calculations: Missing data and logical operators

Lecture 11 - Basics Calculations: Logical operators

Lecture 12 - Basics Calculations: Truth table and conditional executions

Lecture 13 - Basics Calculations: Conditional executions and loops

Lecture 14 - Basics Calculations: Loops

Lecture 15 - Data management - Sequences

Lecture 16 - Data management - sequences

Lecture 17 - Data management - Repeats

Lecture 18 - Data management - Sorting and Ordering

Lecture 19 - Data management - Lists

Lecture 20 - Data management - Lists (Continued...)

Lecture 21 - Data management - Vector indexing

Lecture 22 - Data management - Vector Indexing (Continued...)

Lecture 23 - Data management - Factors

Lecture 24 - Data management - factors (Continued...)

Lecture 25 - Strings - Display and Formatting, Print and Format Functions

Lecture 26 - Strings - Display and Formatting, Print and Format with Concatenate

Lecture 27 - Strings - Display and Formatting, Paste Function

Lecture 28 - Strings - Display and Formatting, Splitting

Lecture 29 - Strings - Display and Formatting, Replacement_ Manipulations _Alphabets

Lecture 30 - Strings - Display and Formatting, Replacement and Evaluation of Strings

Lecture 31 - Data frames

Lecture 32 - Data frames (Continued...)

Lecture 33 - Data frames (Continued...)

Lecture 34 - Data Handling - Importing CSV and Tabular Data Files

Lecture 35 - Data Handling - Importing Data Files from Other Software

Lecture 36 - Statistical Functions - Frequency and Partition values

Lecture 37 - Statistical Functions - Graphics and Plots

Lecture 38 - Statistical Functions - Central Tendency and Variation

Lecture 39 - Statistical Functions - Boxplots, Skewness and Kurtosis

Lecture 40 - Statistical Functions - Bivariate three dimensional plot

Lecture 41 - Statistical Functions - Correlation and Examples of Programming

Lecture 42 - Examples of Programming

Lecture 43 - Examples of More Programming