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 ScienceEducation and Research (IISER) Pune. He received a PhD from the Theoretical 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 IITKharagpur.


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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jul-Oct 2018

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 Syllabus

 Enrollment : 18-Apr-2018 to 30-Jun-2018

 Exam registration : 25-Jun-2018 to 18-Sep-2018

 Exam Date : 28-Oct-2018

Enrolled

1563

Registered

75

Certificate Eligible

53

Certified Category Count

Gold

4

Elite

38

Successfully completed

11

Participation

1

Success

Elite

Gold





Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

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

K.RAVIKUMAR 92%

VNR VIGNANA JYOTHI INSTITUTE OF ENGINEERING &TECHNOLOGY

LOKASANI ESWARA REDDY 91%

XXXXXXX

SANTOSH CHIVUKULA 91%

HITACHI CONSULTING SOFTWARE SERVICES PVT LTD

SANJAY OLI 90%

DAYANANDA SAGAR COLLEGE OF ENGINEERING

RAIKAR SIDDHARTH HARISH 88%

R V COLLEGE OF ENGINEERING

TESYMOL CYRIAC 88%

MUTHOOT INSTITUTE OF TECHNOLOGY & SCIENCE

Enrollment Statistics

Total Enrollment: 1563

Registration Statistics

Total Registration : 75

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.