COURSE UNIT TITLE

: TIME SERIES ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4038 TIME SERIES ANALYSIS COMPULSORY 2 2 0 6

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR ESIN FIRUZAN

Offered to

Course Objective

This course will make the students gain experience in identifying systematic pattern of time series data. They should make predictions based on historical values. Students should apply the techniques which they have learned in this course for making decision any forecasts and long term plans.

Learning Outcomes of the Course Unit

1   To distinguish time series components,
2   To obtain autocovariance function of any stochastic process,
3   To identify Nonseasonal Box-Jenkins models using autocorrelation and partial autocorrelation function,
4   To test significance of parameter estimates of tentatively identified ARIMA (p,d,q) models,
5   To make decisions whether models are adequate,
6   To distinguish between nonseasonal and seasonal models
7   Developing forecasts based on appropriate ARIMA(p,d,q)x(P,D,Q) models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Stationarity in time series
2 Autocorrelation Function
3 Partial Autocorrelation Function
4 Tentatively identification of Nonseasonal Box-Jenkins Models
5 Autoregressive Model AR(p)
6 Moving Average MA(q)
7 Mixed Autoregressive Moving Average Model ARMA(p,q)
8 Midterm exam
9 Estimation-Diagnostic Checking-Forecasting
10 Seasonal Box-Jenkins Models
11 Seasonal Autoregressive Model SAR(P)
12 Seasonal Moving Average Model SMA(Q)
13 Seasonal Mixed Autoregressive Moving Average Model SARMA(P,D,Q)
14 Estimation-Diagnostic Checking-Forecasting

Recomended or Required Reading

Textbook(s): Wei, W.W.S., 2006, Time Series Analysis, Univariate and Multivariate Methods, 2nd EdnPearson

Supplementary Book(s):
Bowerman L. B., O Connell R. T. (1993) Forecasting and Time Series, 3rd Edition, Duxbury

Planned Learning Activities and Teaching Methods

Lecture format, built around the textbook readings and computer applications with numerous examples chosen to illustrate theoretical concepts. Lots of drill with emphasis on practice. Questions are encouraged and discussion of material stressed.
Lecture, project and presentation

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.35 + FIN * 0.35
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.35 + RST * 0.35


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

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of project, presentation and exams

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: esin.firuzan@deu.edu.tr
Tel: 0232 301 85 57

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Tutorials 13 2 26
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 0 0 0
Preparation for final exam 1 35 35
Preparing assignments 7 7 49
Final 1 2 2
Midterm 0 0 0
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.155453
LO.2555
LO.355453
LO.4553
LO.55553
LO.655353
LO.75533453