This three-day course gets you up and running with a set of procedures for analyzing time series data. Learn how to forecast using a variety of models which take into account different combinations of trend, seasonality and prediction variables. Generate predicted values along with standard errors, confidence intervals and residuals. This course will also show you how to display your results graphically so you can see the big picture.
- What is Time Series Analysis?
- Starting Time Series Analysis
- Smoothing Time Series Data
- Looking at the Smooth and the Rough
- Using Moving Averages as Forecasts
- Introduction to Exponential Smoothing
- Measuring Model Performance
- Fitting a Simple Curve to Time Series Data
- Seasonal Decomposition
- Multiple Regression and Autocorrelation
- Autoregressive Models
- Mixed Models and Outliers
- Some Approaches to Modeling a Nonstationary Series
- ARIMA Models for Seasonal Series
- Regression with Autocorrelated Errors
Course Duration: 3 Full Days
Venues: Gauteng and Cape Town
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