Time Series Analysis and Forecasting

The course is for those who would like to learn basic and advanced methods of time series analysis and forecasting. The basic notions are presented, such as stochastic process theory and main features of time series data. Methods presented include trend analysis, seasonality indices, analysis of residuals, autocorrelation function, ANOVA for seasonality checking, ARIMA models and Exponential Smoothing. All methods are ilustrated on real data sets – yearly, quarterly, daily and hourly time series.

For whom?

• For decision makers who would like to based their decisions on time series analysis results and forecasts, e.g. in business, marketing, sales, and enterprise management.
• For scientists and analysts from different disciplines – economics, biology, medicine, demography, macroeconomics, sports, sociology, engineering.

Course results:

• You will learn theoretical basics of time series analysis and forecasting
• You will know how to identify, test, measure and forecast time series components
• You will learn how to build time series models in Statistica, and calculate forecasts