TIME SERIES ANALYSIS AND FORECASTING

About this Course

  • 422 students enrolled
  • 2 instructors

Course Description

This course aims to expose to the students advanced univariate and multivariate regression models for forecasting purposes using time series data. Using computer packages to develop the models using real data is emphasized. The students are expected to be able to develop forecast models and to present the results.

Course Learning Outcomes

1 ) Eloborate solutions to solve problems related to time series analysis and forecasting
2 ) Demonstrate entrepreneurial mind in tasks related to time series analysis and forecasting
3 ) Demonstrate managerial skills in tasks related to time series analysis and forecasting
4 ) Demonstrate social skills in assignments related to time series analysis and forecasting

Course Details

STATUS : Open
DURATION : FLEXIBLE
EFFORT : 3 hours per week
MODE : 100% Online
COURSE LEVEL : Beginner
LANGUAGE : English
CLUSTER : Science & Technology ( ST )

Join this course

 Syllabus

Forecasting Scenario
Definition of time series
Component of time series
Error measures
Within and out-of-sample model evaluation

Concept and ideas
Naive forecast
Average methods
Exponential smoothing methods
Decomposition method

Practical issues and problems
Multi-variables modelling procedure
Specification error and diagnostic testing procedures
Generate (conditional and unconditional) forecast value

Random walk process
Test for stationary
Forecasting under stationary and non-stationary condition

Autoregressive (AR) and Moving Average (MA) modelling
Autocorrelation (AC) and Partial Auto Correlation
Using Backward Shift operator
Model identification
ARMA/ARIMA modelling
Model selection and evaluation

Our Instructor

DR. NORANI BINTI AMIT

 Course Instructor
UiTM Kampus Seremban 3

MUHAMMAD ASMU'I BIN ABDUL RAHIM

 Course Instructor
UiTM Shah Alam

 Frequently Asked Questions

A1 : Basic statistics knowledge.