Shalabh
shalab@iitk.ac.in
shalabh1@yahoo.com
Department of Mathematics & Statistics
Indian
Exploratory Statistical Data Analysis With R Software
Swayam Prabha Course
The course provides an introduction to the tools used in descriptive statistics and their use using R software.
Suggested books:
Introduction to Statistics and Data Analysis - With Exercises, Solutions and Applications in R By Christian Heumann, Michael Schomaker and Shalabh, Springer, 2016
Language of the course: Hindi
Duration of the course: 40 Hours
Swayam Prabha DTH Channel 16 Youtube link: The telecasted lectures are available at YouTube (Click here).
Slides and Videos used in the lectures:
|
Video Lecture links |
Lecture download links |
Lecture Title |
Lecture No. |
|
Click here Lecture 1 |
Click here Lecture 1 |
What is R and How to Learn the Course |
1 |
|
Click here Lecture 2 |
Click here Lecture 2 |
Analysis of Variance and Design of Experiments |
2 |
|
Click here Lecture 3 |
Click here Lecture 3 |
Working with R Software |
3 |
|
Click here Lecture 4 |
Click here Lecture 4 |
Basic Calculations and R as a Calculator |
4 |
|
Click here Lecture 5 |
Click here Lecture 5 |
Built-in Commands and Missing Values |
5 |
|
Click here Lecture 6 |
Click here Lecture 6 |
Operations with Matrices in R |
6 |
|
Click here Lecture 7 |
Click here Lecture 7 |
Introduction to Exploratory Statistical Data Analysis |
7 |
|
Click here Lecture 8 |
Click here Lecture 8 |
Basic Concepts of Exploratory Statistical Data |
8 |
|
Click here Lecture 9 |
Click here Lecture 9 |
Basic Terminologies of Exploratory Statistical Data Analysis |
9 |
|
Click here Lecture 10 |
Click here Lecture 10 |
Data, Frequency and Frequency Distribution |
10 |
|
Click here Lecture 11 |
Click here Lecture 11 |
Frequency Distribution and Cumulative Distribution Functions |
11 |
|
Click here Lecture 12 |
Click here Lecture 12 |
Frequency Distribution with R Software |
12 |
|
Click here Lecture 13 |
Click here Lecture 13 |
Graphics and Plots-Bar Diagrams |
13 |
|
Click here Lecture 14 |
Click here Lecture 14 |
Subdivided Bar Plots and Pie Diagrams |
14 |
|
Click here Lecture 15 |
Click here Lecture 15 |
3D Pie Diagram and Histogram |
15 |
|
Click here Lecture 16 |
Click here Lecture 16 |
Kernel Density and Stem - Leaf Plots |
16 |
|
Click here Lecture 17 |
Click here Lecture 17 |
Central Tendency of Data: Arithmetic Mean |
17 |
|
Click here Lecture 18 |
Click here Lecture 18 |
Central Tendency of Data: Weighted Arithmetic Mean and Partition Values |
18 |
|
Click here Lecture 19 |
Click here Lecture 19 |
Partition Values - Median and Quantiles |
19 |
|
Click here Lecture 20 |
Click here Lecture 20 |
Partition Values - Quantiles |
20 |
|
Click here Lecture 21 |
Click here Lecture 21 |
Mode |
21 |
|
Click here Lecture 22 |
Click here Lecture 22 |
Geometric Mean and Harmonic Mean |
22 |
|
Click here Lecture 23 |
Click here Lecture 23 |
Variation in Data and Measurement of Variability |
23 |
|
Click here Lecture 24 |
Click here Lecture 24 |
Variation Measures based on Range and Quartiles |
24 |
|
Click here Lecture 25 |
Click here Lecture 25 |
Variation Measures based on Absolute Deviations |
25 |
|
Click here Lecture 26 |
Click here Lecture 26 |
Absolute Deviation in R and Measures Based on Squared Deviations |
26 |
|
Click here Lecture 27 |
Click here Lecture 27 |
Mean Squared Error, Variance Standard Deviation and Standard Error |
27 |
|
Click here Lecture 28 |
Click here Lecture 28 |
Variance, Standard Error and Their Computations in R |
28 |
|
Click here Lecture 29 |
Click here Lecture 29 |
Coefficient of Variation and Boxplots |
29 |
|
Click here Lecture 30 |
Click here Lecture 30 |
Raw and Central Moments |
30 |
|
Click here Lecture 31 |
Click here Lecture 31 |
Sheppard's Correction in Moments, Absolute Moments and Computation of Moments in R |
31 |
|
Click here Lecture 32 |
Click here Lecture 32 |
Skewness and Kurtosis |
32 |
|
Click here Lecture 33 |
Click here Lecture 33 |
Association of Variables : Univariate and Bivariate Scatter Plots |
33 |
|
Click here Lecture 34 |
Click here Lecture 34 |
Association of Variables : Smooth Scatter Plots |
34 |
|
Click here Lecture 35 |
Click here Lecture 35 |
Correlation Coefficient |
35 |
|
Click here Lecture 36 |
Click here Lecture 36 |
Correlation Coefficient using R and Rank Correlation Coefficient |
36 |
|
Click here Lecture 37 |
Click here Lecture 37 |
Association of Discrete Variables |
37 |
|
Click here Lecture 38 |
Click here Lecture 38 |
Association of Discrete Variables with R Software |
38 |
|
Click here Lecture 39 |
Click here Lecture 39 |
Fitting of Linear Models : Least Squares Method - One Variable |
39 |
|
Click here Lecture 40 |
Click here Lecture 40 |
Fitting of Linear Models with More than One Variables and R Software |
40 |