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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS YBS 6005 DATA ANALYSIS ELECTIVE 3 0 0 8

Offered By

Management Information Systems

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSISTANT PROFESSOR KUTAN KORUYAN

Offered to

Management Information Systems

Course Objective

To ensure proper use of statistical techniques and analysis, without having to obtain an overview of some statistics and / or edit the data before deciding to perform hypothesis testing

Learning Outcomes of the Course Unit

1   To be able to have a quick and easy information about a particular data 2   To be able to find the extreme observations, and how to correct grip 3   To be able to use of resistant methods 4   To be able to summarize the data and make available for analysis 5   To be able to visualize data

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Steam and leaf method 2 Letter values 3 Box plots 4 Transformation of data 5 Resistant lines 6 Analysis of residuals 7 Transformation of variables to simplify the relationships 8 Smoothing of data 9 Median correction 10 Rotograms 11 Visual multivariate techniques 12 Package programs and applications 13 Student presentations I 14 Student presentations II

Recomended or Required Reading

1. Velleman, P. F. ve Hoaglin, D. C. (1981), Applications, Basics, and Computing of Exploratory Data Analysis, Duxbury Pres, Boston

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 PRJ PROJECT 3 PRS PRESENTATION 4 FIN FINAL EXAM 5 FCG FINAL COURSE GRADE MTE* 0.20 + PRJ* 0.20 + PRS* 0.20 + FIN* 0.40 6 RST RESIT 7 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + PRJ * 0.20 + PRS * 0.20 + 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 4 52 Preparation for midterm exam 1 10 10 Preparation for final exam 1 20 20 Preparing presentations 1 30 30 Preparing report 1 40 40 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 193

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 LO.1 5 3 3 4 LO.2 5 3 3 4 LO.3 5 3 3 4 LO.4 5 3 3 4 LO.5 5 3 3 4