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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EMT 4030 COMPUTER AIDED DATA ANALYSIS ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR EFE SARIBAY

Offered to

Econometrics Econometrics (Evening)

Course Objective

The aim of the course is to convey necessary basic programming algorithms, experimenting with Visual Basic programming language, to design and apply basic relational data programming for advanced levels based on the need.

Learning Outcomes of the Course Unit

1   Understanding the usage areas of Multivariate Statistical Analysis 2   Ability to use dimension reduction methods 3   Ability to use Multivariate Hypothesis tests 4   Ability to use graphical methods in Multivariate Statistical Analysis 5   Ability to apply Multivariate Statistical Analysis in different package programs and software

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to Multivariate Statistical Analysis 2 Factor Analysis 3 Multidimensional Scaling Analysis 4 Compatibility Analysis 5 Multiple Correspondence Analysis 6 Manova 7 Two-way Manova 8 Hotelling T Square Test 9 Midterm 10 Hypothesis Tests in Three-Dimensional Crosstabs 11 ANCOVA 12 Clustering Analysis 13 Clustering Analysis 14 Discriminant Analysis 15 Canonical Correlation Analysis

Recomended or Required Reading

Programing in Visual Basic 6.0, McGraw Hill, Julia Case Bradley, Anita C. Millspaugh

Planned Learning Activities and Teaching Methods

Teaching,Question-Answer,Discussion,Problem solving

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTEG MIDTERM GRADE MTEG * 1 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term mark x 40 Mid-term exam x 100 Final exam mark x 60

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 12 3 36 Preparations before/after weekly lectures 12 2 24 Preparation for midterm exam 1 25 25 Preparation for final exam 1 28 28 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 115

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 PO.9 PO.10 LO.1 1 LO.2 1 LO.3 1 LO.4 1 LO.5 1