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Forecasting
Postgraduate | SWI-STA70004 | 2019
Course information for 2019 intake
Forecast methods to plan and make timely data decisions. Use tools and packages. Get historical about data and chose the right forecasting model. Interpret and apply accuracy measures to ensure model suitability. Estimate future values.
- Study method
- 100% online
- Assessments
- Subject may require attendance
- Entry requirements
- Part of a degree
- Duration
- -
FEE-HELP available
Forecasting
About this subject
Students who successfully complete this subject will be able to:
- Plot time series and describe their characteristics
- Demonstrate fundamental concepts in time series modelling, such as time series decomposition and stationarity
- Compute indices based on time series data
- Appraise the limitations of regression as a forecasting tool
- Demonstrate univariate forecasting methods such as ARIMA and exponential smoothing and identifying appropriate models for a project
- Assess forecast performance using key measures of forecast accuracy such as MSE and MAPE
- Interpret forecast results for a general non-statistical audience.
- Time series forecasting methods
- Measures of accuracy
- Introduction to smoothing methods
- Methods for stationary forecasting
- Methods for trend forecasting
- Seasonal forecasts by smoothing
- Decomposition methods
- Regression and forecasting with cycles
- Removal of non-stationarity
- Interpretation of the autocorrelation function and the partial autocorrelation function
- ARIMA model identification
- SARIMA model identification
This subject introduces students to a range of forecasting methods and their application to planning and decision-making. It teaches teach students about common tools and packages used in forecasting; the use of historical data to identify appropriate forecasting model(s); the use of accuracy measures to check the adequacy of the selected model; and the use the final model to forecast future values.
Please note: assessment values are indicative only, details will be advised at the start of the subject.
- Quizzes — Online (10%)
- Assignments — 2 (40%)
- Invigilated Exam (50%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
To enrol in this subject, you must be admitted into a degree.
Prior study
You must have successfully completed the following subject(s) before starting this subject:
one of
- SWI-STA60005-Statistical Practice 2
SWI-HMS771 (Not currently available)
Equivalent subjects
You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
SWI-HMS782 (Not currently available)
Additional requirements
- Other requirements -
- Other special requirement
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.