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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS VYA 5018 DATA VISUALISATION ELECTIVE 3 0 0 4

Offered By

DATA MANAGEMENT AND ANALYSIS

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR IPEK DEVECI KOCAKOÇ

Offered to

DATA MANAGEMENT AND ANALYSIS

Course Objective

The main objective of the course is to distinguish between data structures,determine summarizing tools and statistical methods in terms of data structure, to present conversion tool making data into more recognisable and readible format , to create smart tables, to report data by using graph tools.

Learning Outcomes of the Course Unit

1   1. To able to determine data structure. 2   2. To able to determine statistical methods and summarization tool fit for data structure. 3   3. To able to report in more readable and recognisable format. 4   4. To able to create smart tables and graphs with the aid of computer program. 5   5. To able to use programming of data visualization.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to data visualisation 2 Data visualisation tips 3 Visualising data with R-1 4 Visualising data with R-1 5 Visualising data with R-1 6 Visualising data with Python-1 7 Visualising data with Python-2 8 Visualising data with Python-3 9 Visualising data with Tableau-1 10 Visualising data with Tableau-2 11 Visualising data with Tableau-3 12 Case studies 13 Case studies 14 Case studies

Recomended or Required Reading

Data Visualisation with R: 100 Examples, Thomas Rahlf Google Charts Tools : https://developers.google.com/chart/

Planned Learning Activities and Teaching Methods

1- Lecture Method, 2- Demonstration Method with Applications, 3-Determined Cases Discussed Analysis Method

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

The weighted average of the midterm grade, the midterm work and the final grade must be 75 and above.

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 14 3 42 Preparations before/after weekly lectures 10 2 20 Preparation for midterm exam 1 10 10 Preparation for final exam 1 10 10 Preparing assignments 5 3 15 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 103

Contribution of Learning Outcomes to Programme Outcomes

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