NOC:Introduction to R Software


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