Course Name: Essentials of Data Science With R Software - 1: Probability and Statistical Inference

Course abstract

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.


Course Instructor

Media Object

Prof. Shalabh

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 22 years of experience in teaching and research. He has developed several web based NPTEL courses including on regression analysis and has conducted several workshops on statistics for teachers, researchers and practitioners. He has received several national and international award and fellowships. He has authored more than 70 research papers in national and international journals. He has written four books and one of the book on linear models is coauthored with Prof. C.R. Rao.
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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jan-Apr 2021

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 Syllabus

 Enrollment : 18-Nov-2020 to 25-Jan-2021

 Exam registration : 15-Jan-2021 to 12-Mar-2021

 Exam Date : 24-Apr-2021

Enrolled

15178

Registered

317

Certificate Eligible

156

Certified Category Count

Gold

19

Silver

49

Elite

52

Successfully completed

36

Participation

29

Success

Elite

Silver

Gold





Legend

AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Essentials of Data Science With R Software - 1: Probability and Statistical Inference - Toppers list
Top 1 % of Certified Candidates

HEMANT TRIVEDI 98%

SINGH SHILANK SUBHASHCHANDRA 97%

DWARKADAS J.SANGHVI COLLEGE OF ENGINEERING


Top 2 % of Certified Candidates

SUVAM BIT 96%

University of Kalyani


Top 5 % of Certified Candidates

BHAVANA NAMBOODIRI 95%

ABDUL MAJID K K 94%

FAROOK COLLEGE

ASHOK SINGH 94%

Hindu college

TEJAS LIPARE 93%

PUNE INSTITUTE OF COMPUTER TECHNOLOGY

RUCHA SIDDAM 93%

FERGUSSON COLLEGE

DAVE SHIVANSHI 93%

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, VADODARA

Enrollment Statistics

Total Enrollment: 15178

Registration Statistics

Total Registration : 318

Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.