Watch the video "Mastering JMP: Analyzing Date/Time Data".
- This is the on-demand version of the webinar held in June 2022. The seminar content has been reconfigured for on-demand use, and introduces JMP's ability to effectively visualize date/time data and analyze time-series data.
- The video consists of two chapters (Chapter1, Chapter2), and each chapter is divided into three sections (Section1 to Section3).
- The JMP format data (.jmp) used in the video can be downloaded from the link at the bottom of this page.
*This seminar uses JMP 16.2, the latest version at the time of video creation (August 2022).
*At the time of the webinar, the function of "Function Data Explorer" was introduced, but it is not included in this on-demand video. We plan to introduce the functions of the "Functional Data Explorer" on another occasion.
Chapter 1: How JMP handles date/time data and how to visualize it effectively
We'll cover the basics of JMP's date/time data format, and then provide an example of how JMP can be used to visualize date/time data. As graphs for visualization, line graphs, smooth lines, regression lines, bar graphs, heat maps, and bubble plots are used.
・Chapter1 Section1 : Basics of Date/Time Data in JMP (10:20)
・Chapter1 Section2 : Analysis example 1 Daily data (13:09)
・Chapter1 Section3 : Analysis example 2 Annual and monthly data (14 minutes 48 seconds)
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Chapter 2: Time Series Prediction with JMP - ARIMA Model, State Space Smoothing Model -
Learn how to use JMP to fit models to time series data and predict future behavior. In JMP, there are two platforms for time series forecasting: "Time Series Analysis" and "Time Series Forecasting". Demonstrate how to fit, select the best model, and make predictions from the fitted model.
・Chapter2 Section1 : Introduction (5 minutes 57 seconds)
・Chapter2 Section2 : Fitting an ARIMA Model with "Time Series Analysis" (18:35)
・Chapter2 Section3 : Fitting a State-Space Smoothing Model by "Time Series Prediction" (18:03)
