Foundational knowledge is a platform for exploration
Ito argues that students do best when they’re given the reins to explore the data for themselves—to experiment with new analyses or generate hypotheses by looking at data from a range of different perspectives. And that’s why JMP is his tool of choice: JMP is at its core an exploratory platform.
Another advantage of using JMP to teach statistics, Ito contends, is that the abundant sample data included in the JMP data library can be used in his classes. "My students use JMP sample data to practice using the software’s many analytical capabilities,” says Ito. “Statistical analysis methods are often best learned in a case study format.”
Ito teaches his students that in biostatistics, even if there is a relationship between variables, it is not necessarily a causal relationship. And occasionally the inverse is also true. As a result, researchers must marry a statistical approach with an observational one, taking into account factors like strength and consistency of relationships, time and biological dose-response gradients.
"One of the many advantages of JMP is the sheer variety of analytical applications it puts at your fingertips,” says Ito. “Whatever the purpose of the analysis—whether the outcome variable is binary, continuous value, survival time, etc.—there is a JMP platform suited for it: distribution summary, comparison between 2 groups, comparison between multiple groups, prognostic factor/stratification adjustments.”
“We structured the curriculum so that students can learn about as many of these methods as possible," he notes. “And I think that the possibilities of JMP script are really big.” The application-oriented nature of the course allows students to explore those lines of inquiry that are most relevant to their field of specialization.
As students become more accustomed to using JMP, Ito observes, they begin to not only analyze data as required for class, but to explore how statistics can be of use to them in their own future scientific studies and research. And this, Ito says, is exactly what he was hoping for.