# GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
FORECASTİNG METHODS/5351303
 Course Title: FORECASTİNG METHODS Credits 3 ECTS 7.5 Course Semester 1 Type of The Course Elective
COURSE INFORMATION
-- (CATALOG CONTENT)
-- (TEXTBOOK)
-- (SUPPLEMENTARY TEXTBOOK)
-- (PREREQUISITES AND CO-REQUISITES)
-- LANGUAGE OF INSTRUCTION
Turkish
-- COURSE OBJECTIVES
-- COURSE LEARNING OUTCOMES
To have knowledge culture analysis of time series and forecasting
To be capable of analyzing and modeling a time series of
Package programs to apply time series topics
Solving a problem or project,is capable of use in preparing the information
Similar problems in other courses disciplines of analysis evaluation of the ability of

-- MODE OF DELIVERY
The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE 1. Week An overview of forecasting univariate time series . What can be forecast? . Determining what to forecast . Forecasting data and methods . Some cas 2. Week Forecasting Tools . Graphics . Numerical data summaries . Some simple forecasting methods . Evaluating forecast accuracy 3. Week Autocorrelation and seasonality 4. Week White noise and time series decomposition . Time series components . Moving averages . Classical decomposition . X-12-ARIMA decomposition . Seas 5. Week Exponential smoothing methods . Simple exponential smoothing . Holt's linear trend method . Exponential trend method . Damped trend methods 6. Week Error-Trend-Seasonal(ETS) models . Holt-Winters seasonal method . A taxonomy of exponential smoothing methods . Innovations state space models for 7. Week Midterm exam 8. Week Brown’s general exponential smoothing method 9. Week Harmonic model ve Fourier analysis of time series dat 10. Week Transformations and adjustments 11. Week Stationarity and differencing 12. Week Autoregressive models 13. Week Moving average models 14. Week Estimation and order selection in ARIMA modelling 15. Week Seasonal ARIMA models 16. Week Final Exam
-- TEACHING and LEARNING METHODS
-- ASSESSMENT CRITERIA
 Quantity Total Weighting (%) Midterm Exams 1 20 Assignment 7 20 Application 0 0 Projects 1 30 Practice 0 0 Quiz 0 0 Percent of In-term Studies 40 Percentage of Final Exam to Total Score 60