Course Name: Regression analysis

Course abstract

Regression analysis is one of the most powerful methods in statistics for determining the relationships between variables and using these relationships to forecast future observations. The foundation of regression analysis is very helpful for any kind of modelling exercises. Regression models are used to predict and forecast future outcomes. Its popularity in finance is very high; it is also very popular in other disciplines like life and biological sciences, management, engineering, etc. In this online course, you will learn how to derive simple and multiple linear regression models, learn what assumptions underline the models, learn how to test whether your data satisfy those assumptions and what can be done when those assumptions are not met, and develop strategies for building best models. We will also learn how to create dummy variables and interpret their effects in multiple regression analysis; to build polynomial regression models and generalized linear models.


Course Instructor

Media Object

Prof. Soumen Maity

Soumen Maity is an Associate Professor of Mathematics at Indian Institute of Science Education and Research (IISER) Pune. He received a PhD from theTheoretical Statistics & Mathematics Unit at Indian Statistical Institute (ISI) Kolkata, India in 2002. He has postdoctoral experience from Lund University,Sweden; Indian Institute of Management (IIM) Kolkata, India; and University of Ottawa, Canada. Prior to joining IISER Pune in 2009, he worked as Assistant Professor at IIT Guwahati and IIT Kharagpur.
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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jul-Oct 2019

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 Syllabus

 Enrollment : 15-May-2019 to 05-Aug-2019

 Exam registration : 01-Jun-2019 to 30-Sep-2019

 Exam Date : 16-Nov-2019, 16-Nov-2019

Enrolled

1724

Registered

95

Certificate Eligible

57

Certified Category Count

Gold

13

Silver

7

Elite

17

Successfully completed

20

Participation

12

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.
Regression analysis - Toppers list

DIVYA A 98%

GOVERNMENT VICTORIA COLLEGE

DR.RAVISHANKAR 97%

Manipal Academy of Higher Education

SANDESH SHRIKANT KURADE 96%

M.E.S. ABASAHEB GARWARE COLLEGE OF ARTS AND SCIENCE, PUNE

TANISH TELISARA 95%

SIES COLLEGE OF ARTS SCIENCE AND COMMERCE

SUSEELATHA ANNAMAREDDY 94%

GAYATRI VIDYA PARISHAD COLLEGE OF ENGINEERING FOR WOMEN

Enrollment Statistics

Total Enrollment: 1724

Registration Statistics

Total Registration : 95

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.