# Exploratory Data Analysis for Data Science with R Software (Hindi)

- Institution: IIT Kanpur
- Department: Computer Science and Engineering
- Teacher: Prof. Shalabh
- Level: Undergraduate
- Language: English
- Subjects: Computer science, Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/106104002)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/106104002)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Any data analysis requires statistical tools. The course describes the basic statistical tools and related concepts used in the exploratory data analysis. The use of analytical and graphical tools in data science will be explained. Their implementation using open-source R software will be demonstrated with the related software commands along with the interpretation of the outcomes of analytical and graphical tools.

Intended audience: All UG students in Mathematics, Engineering, Management

Prerequisites: Mathematics background up to class 10 is needed. Having some preliminary knowledge will be helpful but not necessarily mandatory.

## Lectures

1. [Lecture 0 : How to Learn and Follow the Course](https://invisiblenetwork.ai/learn/nptel/106104002/0bd4acba8c0f) (YouTube)
2. [Lecture 1 : Data Science - Why, What and How?](https://invisiblenetwork.ai/learn/nptel/106104002/f5dae6ee0385) (YouTube)
3. [Lecture 2 : Introduction to R Software](https://invisiblenetwork.ai/learn/nptel/106104002/e281224b3c38) (YouTube)
4. [Lecture 3 : Calculations with R Software - Basics and R as a Calculator](https://invisiblenetwork.ai/learn/nptel/106104002/70616e9ec64d) (YouTube)
5. [Lecture 4 : Calculations with R Software - Calculations with Data Vectors](https://invisiblenetwork.ai/learn/nptel/106104002/2bd20c21da11) (YouTube)
6. [Lecture 5 : Calculations with R Software - Built in Commands and Missing Data Handling](https://invisiblenetwork.ai/learn/nptel/106104002/5a46bbe514a6) (YouTube)
7. [Lecture 6 : Calculations with R Software - Operations with Matrices](https://invisiblenetwork.ai/learn/nptel/106104002/0e563a9fa8ab) (YouTube)
8. [Lecture 7 : Data Preparation - CSV and TXT Data Files](https://invisiblenetwork.ai/learn/nptel/106104002/a819553700ca) (YouTube)
9. [Lecture 8 : Data Preparation - Excel Files and Data Frame](https://invisiblenetwork.ai/learn/nptel/106104002/efd51378cfe8) (YouTube)
10. [Lecture 9 : Introduction to Exploratory Data Analysis - Objectives, Steps and Basic Definitions](https://invisiblenetwork.ai/learn/nptel/106104002/78401e80a07a) (YouTube)
11. [Lecture 10 : Introduction to Exploratory Data Analysis - Variables and Type of Data](https://invisiblenetwork.ai/learn/nptel/106104002/f9bc42258e38) (YouTube)
12. [Lecture 11 : Frequency Distribution - Absolute, Relative and Cumulative Frequencies of Attribute and Discrete Data](https://invisiblenetwork.ai/learn/nptel/106104002/9fbfc759487e) (YouTube)
13. [Lecture 12 : Frequency Distribution - Absolute, Relative and Cumulative Frequencies of Continuous Data](https://invisiblenetwork.ai/learn/nptel/106104002/9e700579be75) (YouTube)
14. [Lecture 13 : Frequency Distribution : Frequency Distribution with R Package](https://invisiblenetwork.ai/learn/nptel/106104002/1f06ad7448a3) (YouTube)
15. [Lecture 14 : Univariate Graphics and Plots - Bar Diagrams](https://invisiblenetwork.ai/learn/nptel/106104002/54d107372dbb) (YouTube)
16. [Lecture 15 : Univariate Graphics and Plots - Subdivided Bar Plots and Pie Diagrams](https://invisiblenetwork.ai/learn/nptel/106104002/ee09d1c8c7b7) (YouTube)
17. [Lecture 16 : Univariate Graphics and Plots - 3D Pie Diagram and Tree Map](https://invisiblenetwork.ai/learn/nptel/106104002/94fb35db8450) (YouTube)
18. [Lecture 17 : Univariate Graphics and Plots - Histogram, Kernel Density and Stem - Leaf Plots](https://invisiblenetwork.ai/learn/nptel/106104002/e205a0f088c7) (YouTube)
19. [Lecture 18 : Univariate Graphics and Plots: Graphics with ggplot2 package](https://invisiblenetwork.ai/learn/nptel/106104002/f9a5f290c028) (YouTube)
20. [Lecture 19 : Univariate Graphics and Plots: Creating Graphics with ggplot2 package](https://invisiblenetwork.ai/learn/nptel/106104002/22190244dcc7) (YouTube)
21. [Lecture 20 : Univariate Graphics and Plots - Bar Diagram and Tree Map with ggplot2](https://invisiblenetwork.ai/learn/nptel/106104002/7524593c3cff) (YouTube)
22. [Lecture 21 : Univariate Graphics and Plots - Grouped Bar and Scatter Diagrams with ggplot2 Package](https://invisiblenetwork.ai/learn/nptel/106104002/ae2230ea88d4) (YouTube)
23. [Lecture 22 : Univariate Graphics and Plots - Histogram, Dot Chart and Kernel Density Plots with ggplot2](https://invisiblenetwork.ai/learn/nptel/106104002/05bed3b7fa30) (YouTube)
24. [Lecture 23 : Central Tendency of Data - Arithmetic Mean](https://invisiblenetwork.ai/learn/nptel/106104002/6c6a3e6635ad) (YouTube)
25. [Lecture 24 : Central Tendency of Data - Median](https://invisiblenetwork.ai/learn/nptel/106104002/e3c4b888ee90) (YouTube)
26. [Lecture 25 : Central Tendency of Data - Quantiles](https://invisiblenetwork.ai/learn/nptel/106104002/81c5792379d8) (YouTube)
27. [Lecture 26 : Central Tendency of Data - Mode](https://invisiblenetwork.ai/learn/nptel/106104002/9c5b30dbb170) (YouTube)
28. [Lecture 27 : Central Tendency of Data - Geometric Mean and Harmonic Mean](https://invisiblenetwork.ai/learn/nptel/106104002/3986863b782d) (YouTube)
29. [Lecture 28 : Variation in Data - Range, Interquartile Range and Quartile Deviation](https://invisiblenetwork.ai/learn/nptel/106104002/a922e184a9a3) (YouTube)
30. [Lecture 29 : Variation in Data - Absolute Deviation and Absolute Mean Deviation](https://invisiblenetwork.ai/learn/nptel/106104002/b7689778f60c) (YouTube)
31. [Lecture 30 : Variation in Data - Mean Squared Error, Variance and Standard Deviation](https://invisiblenetwork.ai/learn/nptel/106104002/7841a05abc93) (YouTube)
32. [Lecture 31 : Variation in Data - Computation of Variance and Standard Error with R](https://invisiblenetwork.ai/learn/nptel/106104002/5ad6e6fb648e) (YouTube)
33. [Lecture 32 : Variation in Data - Coefficient of Variation and Summary](https://invisiblenetwork.ai/learn/nptel/106104002/4f4a5f8f7f8f) (YouTube)
34. [Lecture 33 : Variation in Data - Box Plots and Violin Plots](https://invisiblenetwork.ai/learn/nptel/106104002/3897525c1cef) (YouTube)
35. [Lecture 34 : Moments - Raw, Central and Absolute Moments](https://invisiblenetwork.ai/learn/nptel/106104002/ff1753acdb96) (YouTube)
36. [Lecture 35 : Moments - Computation of Moments in R](https://invisiblenetwork.ai/learn/nptel/106104002/024eb05b8a81) (YouTube)
37. [Lecture 36 : Moments - Skewness and Kurtosis](https://invisiblenetwork.ai/learn/nptel/106104002/eb76bb3cae66) (YouTube)
38. [Lecture 37 : Scaling of Data - Centering, Scaling and Z- Scores](https://invisiblenetwork.ai/learn/nptel/106104002/b08bb121eff1) (YouTube)
39. [Lecture 38 : Association of Variables - Scatter and Smooth Scatter Plots](https://invisiblenetwork.ai/learn/nptel/106104002/61435e658968) (YouTube)
40. [Lecture 39 : Association of Variables - Line Chart, Time Series Plot and Bubble Chart](https://invisiblenetwork.ai/learn/nptel/106104002/4d3286697ac3) (YouTube)
41. [Lecture 40 : Association of Variables - Quantile- Quantile Plot](https://invisiblenetwork.ai/learn/nptel/106104002/82324bc3e1f8) (YouTube)
42. [Lecture 41 : Association of Variables - Three Dimensional Plots, Heat Maps and Word Cloud](https://invisiblenetwork.ai/learn/nptel/106104002/87325f556e9e) (YouTube)
43. [Lecture 42 : Association of Variables - Correlation Coefficient](https://invisiblenetwork.ai/learn/nptel/106104002/d1d0ace0c8f4) (YouTube)
44. [Lecture 43 : Association of Variables - Correlation Coefficient using R Software](https://invisiblenetwork.ai/learn/nptel/106104002/7ab7bf66e74a) (YouTube)
45. [Lecture 44 : Association of Variables - Rank Correlation Coefficient](https://invisiblenetwork.ai/learn/nptel/106104002/aabd9bb8448e) (YouTube)
46. [Lecture 45 : Association of Variables - Measures of Association for Discrete and Counting Variables : Bivariate Frequency and Contingency Tables](https://invisiblenetwork.ai/learn/nptel/106104002/c9ea41658713) (YouTube)
47. [Lecture 46 : Association of Variables: Measure of Association for Discrete and Counting Variables with R Commands: Contingency Table, Chi-Squared Statistic, Cramer`s V Statistic and Contingency Coefficient](https://invisiblenetwork.ai/learn/nptel/106104002/b1bdb24d2e14) (YouTube)
48. [Lecture 47 : Modelling of Variables : Least Square Method - One Variable](https://invisiblenetwork.ai/learn/nptel/106104002/fb8dc47d5bb1) (YouTube)
49. [Lecture 48 : Modelling of Variables: Least Squares Method-More than One Variable and R Commands](https://invisiblenetwork.ai/learn/nptel/106104002/44519502fa11) (YouTube)
50. [Lecture 49 : Handling Text Data: Basic Operations with Text and Strings](https://invisiblenetwork.ai/learn/nptel/106104002/7987069d51ea) (YouTube)
51. [Lecture 50 : Handling Text Data: Operations for Finding Patterns in Text Data with Pipe Operator](https://invisiblenetwork.ai/learn/nptel/106104002/2608264067df) (YouTube)
52. [Lecture 51 : Handling Text Data: Operations for Finding Patterns in Text Data without Pipe Operator](https://invisiblenetwork.ai/learn/nptel/106104002/71317288d4c4) (YouTube)
53. [Lecture 52 : Handling Text Data: Analysis Or Text Data - Frequency & Plots](https://invisiblenetwork.ai/learn/nptel/106104002/ba80902b2a85) (YouTube)
54. [Lecture 53 : Selection of Sample : Simple Random Sampling](https://invisiblenetwork.ai/learn/nptel/106104002/cd29798c3002) (YouTube)
55. [Lecture 54 : Selection of Sample : Simple Random Sampling with R](https://invisiblenetwork.ai/learn/nptel/106104002/17255514a0bb) (YouTube)
56. [Lecture 55 : EDA with Multivariate Data: Sum and Mean Vectors](https://invisiblenetwork.ai/learn/nptel/106104002/e82be95ccbab) (YouTube)
57. [Lecture 56 : EDA with Multivariate Data: Covariance and Correlation Matrices](https://invisiblenetwork.ai/learn/nptel/106104002/ee327b99c9b9) (YouTube)