Essentials Of Data Science With R Software - 1: Probability And Statistical Inference

By Prof. Shalabh | IIT Kanpur

Learners enrolled: 3161

About the course:
Any data analysis is incomplete without statistics. After getting the data, the statistical tools aims to extract the information hidden inside the data. The main objective of statistics is to work on a small sample of data but provide conclusions for the whole population. Such results cannot be obtained without learning the concepts and tools of theory of probability and statistical inference. With the advent of data science, it has become important to learn those tools from computational and data based aspects. Without learning the basic fundamentals of probability theory and statistical inference, it is difficult to implement them correctly on the data and draw correct statistical conclusions. Such fundamental topics have enormous applicability in data science and are to be learnt from data based computational perspectives through software. How to use them with the popular and freely available R statistical software and how to understand the correct statistical inferences is the objective of the course to be taught.

INTENDED AUDIENCE : UG students of Science and Engineering. Students of humanities with basic mathematical and statistical background can also do it. Working professionals in analytics can also do it.

PREREQUISITES : “Introduction to R Course” is preferred. Mathematics background up to class 12 is needed. Some minor statistics background is desirable.

INDUSTRIES SUPPORT : All industries having R & D set up will use this course.

Summary

Course Status :	Completed
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	Mathematics
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	23 Jan 2023
End Date :	14 Apr 2023
Enrollment Ends :	06 Feb 2023
Exam Registration Ends :	17 Mar 2023
Exam Date :	30 Apr 2023 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1:Introduction to data science, basic calculations with R Software and probability theory

Week 2:Probability theory and random variables

Week 3: Random variables and Discrete probability distributions

Week 4:Continuous probability distributions

Week 5:Sampling distributions and Functions of random variables

Week 6:Convergence of random variables, Central limit theorems and Law of large numbers

Week 7: Statistical inference and point estimation

Week 8:Methods of point estimation of parameters

Week 9:Point and confidence interval estimation

Week 10:Confidence interval estimation and test of hypothesis

Week 11: Test of hypothesis

Week 12:Test of hypothesis for attributes and other tests

Books and references

1. Introduction to Statistics and Data Analysis With Exercises, Solutions and Applications in R Authors: Heumann, Christian, Schomaker, Michael, Shalabh, Publisher” Springer 2016

2. Applied Statistics and Probability for Engineers, Douglas C. Montgomery, George C. Runger, 2018, Wiley (Low price edition available)

3. Introduction to. Mathematical. Statistics. Robert V. Hogg. Allen T. Craig,, Low price Indian edition by Pearson Education

4. Probability and Statistics for Engineers. Richard A. Johnson, Irwin Miller, John Freund

5. Mathematical Statistics with Applications. Irwin Miller, Marylees Miller, Pearson Education

6. The R Software-Fundamentals of Programming and Statistical Analysis -Pierre Lafaye de Micheaux, Rémy Drouilhet, Benoit Liquet, Springer 2013

7. A Beginner's Guide to R (Use R) By Alain F. Zuur, Elena N. Ieno, Erik H.W.G. Meesters, Springer 2009

Instructor bio

Prof. Shalabh

IIT Kanpur

Dr. Shalabh is a Professor of Statistics at IIT Kanpur. His research areas of interest are linear models, regression analysis and econometrics. He has more than 23 years of experience in teaching and research. He has developed several web based and MOOC courses in NPTELincluding on regression analysis and has conducted several workshops on statistics for teachers, researchers and practitioners. He has received several national and international awards and fellowships. He has authored more than 75 research papers in national and international journals. He has written four books and one of the book on linear models is co- authored with Prof. C.R. Rao.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 30 April 2023 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kanpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team

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