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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 5071 EXPLANATORY DATA ANALYSIS ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR MURAT TANIK

Offered to

Econometrics

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 Mid-term 9 Smoothing of data 10 Smoothing of data 11 Rotograms 12 Visual multivariate techniques 13 Package programs and applications 14 Applications

Recomended or Required Reading

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

Lecture Method, Proof Method, Discussion Method and Problem Solving 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 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

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