COURSE UNIT TITLE

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR NESLIHAN DEMIREL

Offered to

Statistics
Statistics
STATISTICS

Course Objective

This course will cover alternative methods such as Weighted Least Squares Regression, Ridge Regression and Lasso Regression methods when the assumptions of the multiple linear regression model are not met and this course also include logistic regression model and many popular regression and classification methods such as regression and classification trees and random forest. Students will learn how to evaluate the performance of these methods. They will use R software to implement the methods.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

Draper, N. R., & Smith, H. (1998). Applied regression analysis (Vol. 326). John Wiley & Sons.
Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005). Applied linear statistical models (Vol. 5). New York: McGraw-Hill Irwin.
Mendenhall, W., Sincich, T., & Boudreau, N. S. (1996). A second course in statistics: regression analysis (Vol. 5). Upper Saddle River, NJ: Prentice Hall.
James, G., Witten, D., Hastie, T., Tibshirani, R. (2013). An Introduction to Statistical Learning with Applications in R. Springer, New York.

Planned Learning Activities and Teaching Methods

Lecture, class discussion, homeworks.

Assessment Methods

Further Notes About Assessment Methods

None

Assessment Criteria

Assignments, Midterm and Final exams

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Faculty of Science, Department of Statistics
e-mail: neslihan.ortabas@deu.edu.tr
Tel: 0232 301 86 00

Office Hours

Send an e-mail: neslihan.ortabas@deu.edu.tr for a meeting request

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes