White Papers

• White Paper On 100 Years of the Shewhart Control ChartIn this paper, William H. Woodall commemorates the 100th anniversary of the control chart with some ideas on how to make fuller use of them. Readers will also receive practical advice on how one might achieve the best results implementing statistical process monitoring.
• Tech Brief How to Navigate the Top Seven Pitfalls of Data PrepWhile data cleanup has its obstacles, it is possible to reduce, or even eliminate, the impact of common challenges when preparing data for analysis.
• White Paper Data Visualization and Model BuildingIn this paper, Richard De Veaux, Williams College, explains how visualization and data exploration can be used to draw conclusions about sports performance as we age.
• White Paper The Why and How of Asking Good QuestionsChristine Anderson-Cook discusses how and why asking good questions helps shape curiosity and makes you a better collaborator.
• White Paper Choosing the Right Design - with an Assist from JMP's Design ExplorerDeciding what data to collect for an experiment is a critical decision that has substantial consequences. In this paper, you'll learn how JMP's Design Explorer gives data scientists an easy way to construct and contrast multiple experimental designs that can be compared and evaluated.
• White Paper The Top 7 Myths That Lead to Really Bad GraphsIn this brief, we review seven of the most common misconceptions when visualizing data. When these myths are dispelled, your charts will be more effective and easier to design.
• White Paper Moving from Minitab to JMP: A Transition Guide, Version 2This guide explains how Minitab and JMP differ in the handling of descriptive statistics and visualizations. It is meant to ease the user’s transition from Minitab v19 to JMP 16 and JMP Pro 16. Focus is on the user interface, how tools are accessed, how analyses are performed, and the general workflow of the packages.
• White Paper Moving from SPSS to JMP: A Transition GuideThis guide explains how SPSS and JMP differ in the handling of descriptive statistics and visualizations. It is meant to ease the user’s transition from SPSS Version 27 to JMP 16 and JMP Pro 16.
• White Paper JMP takes the struggle out of data wranglingThis paper provides an introduction to the unglamorous, time-consuming, laborious, and sometimes dreaded “dirty work” of statistical investigations – data preparation. The good news: JMP can perform these operations with ease.