COURSE UNIT TITLE

: ASSESSMENT OF INFLUENCE IN REGRESSION

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 6009 ASSESSMENT OF INFLUENCE IN REGRESSION ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR AYLIN ALIN

Offered to

Statistics
Statistics
STATISTICS

Course Objective

This course will include the information about residuals and residual based methods that are used to detect influentail observations.

Learning Outcomes of the Course Unit

1   nderstanding the role of hat matrix
2   Distinguishing the residual types
3   Applying appropriate transformation
4   Understanding the role of influence curve
5   Obtaining the sample influence curve

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The ordinary residuals
2 Other types of Residuals
3 An algorithm for fitting generalized linear models; Plotting methods and examples
4 Families of transformations; Selecting a transformation; Invariance, Normality, Choice of model and scaling the predictors; Inference
5 Diagnostic methods; Application to power family; Transforming the explanatory variables
6 The influence curve; The influence curve in the linear model, Homework 1
7 Sample versions of influence curve
8 Applications of the sample influence curve
9 Multiple cases
10 Volume of confidence ellipsoids, Homework 2
11 The Andrews and Pregibon diagnostics
12 Predictive influence
13 A general definition of residuals; A general approoach to influence; Logistic regression and generalized linear models, Homework 3
14 Robust regression

Recomended or Required Reading

Textbook:
Cook, R.D, Weisberg, S., Residuals and Influence in Regression , 1982, New York, Chapman and Hall.

Planned Learning Activities and Teaching Methods

Lecture, Homeworks

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG 1 ASSIGNMENT 1
2 ASG 2 ASSIGNMENT 2
3 ASG 3 ASSIGNMENT 3
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE ASG 1 + ASG 2 + ASG 3/3 * 0.40 + FIN * 0.60
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) ASG 1 + ASG 2 + ASG 3/3 * 0.40 + RST * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homework assignments and final exam.

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 Fen Fakültesi Istatistik Bölümü
e-mail: aylin.alin @deu.edu.tr
Tel: 0232 301 85 72

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 13 3 39
Preparation for final exam 1 36 36
Preparing assignments 3 25 75
Final 1 2 2
TOTAL WORKLOAD (hours) 194

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15555
LO.25555
LO.35555555
LO.455555
LO.555555