Based on period of collection, statistical data may be classified into two types: cross-sectional and time series. The former are gathered in a single period, while the latter are collected over equally-spaced time periods. This course will focus on analysis of such time-bounded data. From classical forecasting methods to modern procedures, participants will be tasked to produce a model for their own datasets.

Course Aim

Enhance capacity of course participants to employ projection and forecasting techniques, using Philippine time series data. Specifically, it aims to introduce descriptive analysis, projection and forecasting of time series, as well as the use of non-structural statistical models, including exponential smoothing procedures and ARIMA models. At the end of the course, the participant should be familiar with: key phrases, concepts, and tools used in time series analysis (statistical projection and forecasting), econometric modeling and time series analysis.

Course Participants

Technical staff involved in the analysis of data, especially time series. They should have knowledge of basic statistical concepts and regression analysis.

Course Coverage

Introduction to Statistical Modeling of Time Series
Descriptive Analysis of Time Series
Classical Time Series
Introduction to Seasonal Adjustment
Introduction to ARIMA Modeling
The ARIMA Models
Forecasting Using ARIMA
Introduction to Classical Linear Regression
Introduction to Regression
Linear Regression Model with Autocorrelated Errors

• The Model Equation and Stochastic Assumptions
• The Model Building Procedure

Course Duration: 36 hours/5 days

Registration:

To register and further inquiry, please contact the Training Division at Telefax Nos. (632) 436-1426/9297543 or email it to japebenito@srtc.gov.ph or cemojica@srtc.gov.ph.

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