How to Learn and Follow the Course

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Lecture 01 - Why R and Installation Procedure

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Lecture 02 : Introduction _Help_ Demo examples_ packages_ libraries

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Lecture 03 : Introduction _Command line_ Data editor _ Rstudio

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Lecture 04 : Basics in Calculations

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Lecture 05 : Basics of Calculations _ Calculator _Built in Functions Assignments

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Lecture 06 : Basics of Calculations _Functions _Matrices

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Lecture 07 - Basics Calculations: Matrix Operations

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Lecture 08 - Basic calculations: Matrix operations

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Lecture 09 - Basic calculations: Missing data and logical operators

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Lecture 10 - Basic calculations: Logical operators

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Lecture - 11 Basics calculations: Truth table and conditional executions

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Lecture 12 - Basics calculations: Conditional executions and loops

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Lecture 13 - Basics calculations: Loops

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Lecture 14 - Data managment: Sequences

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Lecture 15 - Data management : sequences

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Lecture 16 - Data management : Repeats

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Lecture 17 - Data management : Sorting and Ordering

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Lecture 18 - Data management : Lists

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Lecture 19 - Data management: Lists (continued)

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Lecture 20 - Data management : Vector indexing

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Lecture 21 - Data management : Vector Indexing (continued)

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Lecture 22 - Data management: Factors

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Lecture 23 - Data management: factors (continued)

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Lecture 24: Strings -Display and Formatting, Print and Format Functions

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Lecture 25 : Strings - Display and Formatting, Print and Format with Concatenate

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Lecture 26 : Strings - Display and Formatting, Paste Function

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Lecture 27 : Strings - Display and Formatting, Splitting

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Lecture 28 : Strings - Display and Formatting, Replacement_ Manipulations _Alphabets

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Lecture 29 : Strings - Display and Formatting, Replacement and Evaluation of Strings

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Lecture 30 : Data frames

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Lecture 31 : Data frames (Continued )

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Lecture 32 : Data frames (Continued)

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Lecture 33 : Data Handling - Importing CSV and Tabular Data Files

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Lecture 34: Data Handling - Importing Data Files from Other Software

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Lecture 35 : Statistical Functions : Frequency and Partition values

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Lecture 36 : Statistical Functions - Graphics and Plots

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Lecture 37 : Statistical Functions - Central Tendency and Variation

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Lecture 38 : Statistical Functions - Boxplots, Skewness and Kurtosis

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Lecture 39 : Statistical Functions - Bivariate three dimensional plot.

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Lecture 40 : Statistical Functions - Correlation and Examples of Programming

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Lecture 41: Examples of Programming

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Lecture 42 : Examples of More Programming

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Live Session 21-10-2020

Preview 48:35

Live Session 04-11-2019

Preview 61:09