As data volumes continue to grow, analysts, business users and students must rely on increasingly sophisticated techniques to extract meaningful, actionable information from their data. JMP is proof that they won’t have to sacrifice ease of use for predictive power: With JMP, popular data mining and forecasting tools are accessible to students, teachers and professionals in a wide variety of disciplines.
The Partition and Stepwise Regression platforms help users determine which of the explanatory variables in their data offer the most insight, while tools such as Principal Components Analysis and Factor Analysis enable users to make better sense of “wide” data sets (often involving dozens or even hundreds of variables) by constructing a handful of new variables, losing very little predictive power in the process. JMP’s forecasting tools, which include ARIMA and exponential smoothing models, help to predict what the future values of a series may look like, given its past values.
Now, we’ve made it even easier for new users of JMP to harness the power of these techniques, by adding to our collection of One-Page Guides, which are available in the Learning Library. These One-Page Guides offer instructions, screenshots and tips for analyzing data with JMP. More than 40 are already posted, with more on the way. The latest additions include: