COURSE UNIT TITLE

: COMPUTER SUPPORTED DATA ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EMT 4018 COMPUTER SUPPORTED DATA ANALYSIS COMPULSORY 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 (Evening)
Econometrics

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   To be able to define benefits and necessity of computer programming in daily activities
2   To be able to explain advanced database programming principles
3   To be able to distinguish variable structures and their differences in database applications
4   To be able to apply computation procedures in database
5   To be able to carry out practical aspects of computer programming
6   To be able to use application softwares at suggested level
7   To be able to carry out a computer programming project

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Instalization of R and Introduction
2 Arithmetic calculations, Variables, Functions, Vectors and Matrices
3 Basic Programming (IF, FOR and WHILE LOOPS)
4 Basic Programming with Exercises
5 Additional R Concepts (Factors, Data Frames and Lists)
6 Descriptive Statistics
7 Handling Missing Data Issue
8 Mid-term exam
9 Sophisticated Data Structures
10 Graphics
11 Input and Output
12 Programming with Functions
13 Numeric Integral
14 Regression Analysis
15 General Exercises

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


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

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/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.11
LO.21
LO.31
LO.41
LO.51
LO.61
LO.71