This course discusses the fundamentals of modeling time series data. The course focuses on the applied use of the three main model types used to analyze univariate time series: exponential smoothing, autoregressive integrated moving average with exogenous variables (ARIMAX), and unobserved components (UCM).
The e-learning format of this course includes Virtual Lab time to practice.
Aprenda a
- Create time series data.
- Accommodate trend, as well as seasonal and event-related variation, in time series models.
- Diagnose, fit, and interpret exponential smoothing models, ARIMAX models, and unobserved components models.
- Identify relative strengths and weaknesses of the three model types.
A quién va dirigido
Analysts with a quantitative background as well as non-statistical analysts and domain experts who would like to augment their time series modeling proficiency
Formatos disponibles | Duración | | |
Live Web: |
4 sesiones de medio día |
e-learning: |
14 horas/180 día licencia |
|
Before attending this course, you should have an understanding of basic statistical concepts. You can gain this experience by completing the Estadística 1: Introducción a ANOVA, Regresión y Regresión Logística course.
Este curso utiliza SAS/ETS, SAS Studio software.