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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 6115 TIME SERIES ANALYSIS ELECTIVE 3 0 0 7

Offered By

Econometrics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR RABIA ECE OMAY

Offered to

Econometrics

Course Objective

Data acquisition, classification and properties of functions used to determine the Time-series models. To learn the use of models for the system to be controlled and predicted.

Learning Outcomes of the Course Unit

1   To be able to explain the features of TS data. 2   To be able to read TS graphs. 3   To be able to interpret various functions of TS data. 4   To be able to model TS data mathematically. 5   To be able to make predictions based on TS data. 6   To be able to measure the reliability of TS analyses.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Notation and terminology 2 Classification of TS data 3 Stationarity, seasionality, trend concepts 4 Autocorrelation, partial- Autocorrelation, Wold decomposition theorem 5 Autoregressive model 6 Moving- average model 7 Autoregressive Moving- average model 8 mid-term 9 Seasonal autoregressive Moving- average model 10 Important issues on modeling 11 Single variable prediction process 12 Multivariate prediction process 13 Model estimation 14 Model validation

Recomended or Required Reading

1- The Analysis of Time Series, C. Chatfield, Chapman and Hall, 1991 2- Time Series Analysis and Forecasting, O.D. Anderson, Butterworths, 1977

Planned Learning Activities and Teaching Methods

Lecture Method, Question-Answer Method, Discussion and Problem Solving Method Metodu- Applications

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

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 35 35 Preparation for final exam 1 35 35 Preparing assignments 1 10 10 Preparing presentations 1 10 10 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 187

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