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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 5067 MULTIVARIATE STATISTISCAL ANALYSIS ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR RABIA ECE OMAY

Offered to

Econometrics DATA MANAGEMENT AND ANALYSIS

Course Objective

The main objective of the course is to do statistical evaluation, interpretation of multivariate data on economics and management science, to give skills about using calculations, formules and statistical results and to achieve multivariate data analysis applications.

Learning Outcomes of the Course Unit

1   To be able to express multivariate data as graphically. 2   To be able to apply hypothesis tests about multivariate data. 3   To be able to achieve and to interpret multivariate quality control applications 4   To be able to achieve and to interpret multivariate variance analysis applications. 5   To be able to achieve and to interpret principle components analysis applications.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Hotelling T2 and Likelihood Ratio Test 2 Hotelling T2 and Likelihood Ratio Test and Applications 3 Confidence interval Theory 4 Confidence interval Theory and Applications 5 Multivariate Quality Control Cards 6 Multivariate Quality Control Cards and Applications 7 Multivariate Variance Analysis 8 Mid-term 9 Multivariate Variance Analysis and Applications 10 Multivariate Linear Regression Model 11 Multivariate Linear Regression Model more 12 Principle Components Analysis 13 Principle Components Analysis more 14 Principle Components Analysis and Applications

Recomended or Required Reading

Applied Multivariate Statistical Analysis, Prentice Hall, Rıchard A. Johnson, Dean W. Wıchern

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 STT TERM WORK (SEMESTER) 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 2 26 Preparation for midterm exam 1 30 30 Preparation for final exam 1 30 30 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 131

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 LO.1 1 1 1 LO.2 1 1 1 LO.3 1 1 1 LO.4 1 1 1 LO.5 1 1 1