JMP Software: Identifying and Modeling Process Cycles
Duration: 1.0 day CEU: 0.6
This course teaches you how to identify and model continuous process data. You participate in interactive demonstrations of JMP software in realistic scenarios.
Learn how to
- identify and model continuous process data
- use ARIMA, seasonal, and nonseasonal models
- identify the magnitude and periods of cycles in process data
Who should attend
Engineers, scientists, and Six Sigma practitionersPrerequisites
Before attending this course, you should have completed the JMP Software: ANOVA and Regression course or have equivalent experience.Course Contents
Stationary Models- identifying time series fundamentals
- measuring and assessing serial dependence
- presenting time series data structures
- presenting time series model-building methodology
- describing simple moving average models
- fitting autoregressive moving average (ARMA) models
- investigating non-stationary models
- producing, saving, and plotting forecasts
- using spectral analysis
- modeling cycles with sine and cosine functions
- modeling cycles with dummy variables
- fitting seasonal ARIMA models