Skills you'll gain

There are 9 modules in this course

By the end of this course, students will be able to: - Describe important time series models and their applications in various fields. - Formulate real life problems using time series models. - Use statistical software to estimate models from real data and draw conclusions and develop solutions from the estimated models. - Use visual and numerical diagnostics to assess the soundness of their models. - Communicate the statistical analyses of substantial data sets through explanatory text, tables, and graphs. - Combine and adapt different statistical models to analyze larger and more complex data.

Module 2: Basic Analysis of Stationary Processes

Module 3: ARMA processes and their Autocorrelation Functions

Module 4: More About the ACF; Best Linear Predictors, Autocorrelation, and Partial Autocorrelation

Module 5: Fitting Data to ARMA models

Module 6: Diagnostics and Order Selection

Module 7: Nonstationary processes: ARIMA and SARIMA Models

Module 8: More on Forecasting

Summative Course Assessment

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