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.

Who should attend?

• 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
• Scientists and analysts from different disciplines – economics, biology, medicine, demography, macroeconomics, sports, sociology, engineering

What will you learn?

• 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

Training programme:

1. Random variables. Statistical inference – estimation and hypotheses testing
2. Stochastic processes and time series
   • Stochastic process definition
   • Time series and its visual representations
   • Stochastic process parameters – expected value, variance, autocorrelation function
   • Stationarity
3. Classical decomposition of time series
   • Indices of dynamics
   • Trend estimation
     • Moving averages
     • Trend function fitting
   • Seasonality identification and analysis
   • Time series detrending aand elimination of seasonal component
4. Regression models in time series analysis
   • Models with dummy variables
   • Classical autoregression models
   • Applying extra variables to time series analysis
   • Trends for uni-named time points
   • Evaluation of models and forecasts
5. ARIMA models
   • Identification
   • Estimation
   • Diagnostic checking
   • Analysis of residuals
6. Exponential Smoothing
   • Basic idea of exponential smoothing
   • Exponential smoothing for time series with trend and seasonality

Training hours: 8:15 AM – 3:30 PM

The training includes:

• comprehensive training materials
• certificate of participation
• coffee breaks and lunch (for on-site training)

Training types:

• online or on-site
• the format is indicated with the training date

For online trainings:

• live sessions via MS Teams
• real-time interaction with the instructor

Prerequisites:

• computer skills in a Windows environment
• basic knowledge of Statistica software
• we recommend prior participation in the course: Statistica – A quick start

Price: 930 EUR net

Price for academic Statistica users with an active StatSoft Polska support agreement (-15%)*: 791 EUR net