Time Series Data Analysis with the Statistical Analysis Software JMP
No code needed! Visualize, analyze, and predict business data with just mouse operations.
Many of the data handled by companies, such as sales, inventory levels, and sensor measurements, are recorded over time as "time series data." The situations in which such data is handled have been increasing in recent years. In this seminar, we will use real time series data as a subject to explain everything from the visualization of time series data to the quantification of factors through regression, forecasting using time series models, and what-if analysis, with demonstrations included. When it comes to regression, it is important to pay attention to the points where previous and subsequent values are related (autocorrelation), but by using time series models that leverage this characteristic, accurate predictions can be made. You will gain tips on how to handle data uniquely with JMP and insights on how to utilize business data for forecasting and decision-making. 【Target Audience】 ■ Individuals in sales, marketing, and planning departments who handle business data such as sales, demand, and inventory. ■ Individuals in manufacturing and technical departments who handle time series data such as sensor, production, and quality data. ■ Those interested in analyzing time series data and looking to learn more. If you do not have JMP, you can participate using a 30-day free trial version. Trial: https://www.jmp.com/ja/download-jmp-free-trial
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Date and Time: August 27, 2026 (Thursday) 14:00–15:30 (Online seminar using Zoom) [Main Content] Using real time series data as a subject, we will convey the following topics with a JMP demonstration: ■ Benefits and important considerations for analyzing time series data with JMP (date handling, lag functions, etc.) ■ Visualization of time series data (analysis using line graphs and smoothing lines) ■ Quantification of factors using regression models ■ Future forecasting and what-if analysis using time series models (ARIMA, smoothing) ■ Features and differentiation of JMP's platform "Time Series Analysis" and "Time Series Forecasting"
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Free (pre-registration is required)
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Applications/Examples of results
"Democratization of Data" and Sharing the "Wisdom" of Manufacturing Across the Company - TOTO's New Quest for "Quality Products and Homogeneity" [Challenge] The manufacturing of sanitary ceramics using natural raw materials involves approximately 13% shrinkage during the drying and firing processes. As products become larger and more complex, the challenge is how to maintain "homogeneous" high quality and convert the "tacit knowledge" of skilled artisans into "explicit knowledge" to pass on to the next generation. This has been a significant issue at TOTO Ltd., which has a history of over 100 years and is fundamental to the company's manufacturing. [Solution] An "exploratory data analysis" using JMP was introduced for the manufacturing data from the advanced Shiga factory. By deepening the high yield achieved through the introduction of the first barcode system in the sanitary ceramics factory, we quantified the "good product conditions" using visual verification with graph builders, as well as partitioning and cluster analysis, leading to improvements in direct yield rates and overall yield. Additionally, JMP was adopted for the foundational education of the "in-house study abroad program" over two years, aiming to elevate company-wide data science skills. [Result] Please check the following page for details! https://www.jmp.com/ja/customer-stories/toto
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The JMP story goes back to 1989 when John Sall decided to combine statistical analysis capabilities with graphical visualizations to animate and visualize data. For more than 35 years now, John Sall has led JMP R&D, making each version of JMP more visual, more interactive, and more practical to help users understand their data. What started as a passion project has grown by leaps and bounds. It’s now a family of statistical software products designed with scientists and engineers in mind and used worldwide in nearly every industry.







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