Semiconductor engineering is a data intensive process. Engineers need to visualize and analyze vast amounts of data to improve yield, identify and rectify drifts or failures, monitor process health, and more. JMP statistical software, used widely in the semiconductor industry, is a strong tool for teaching students in semiconductor engineering and related fields the statistical methods they’ll need to thrive in their careers.

This webinar provides a broad overview of the utility of the JMP Student Edition for teaching statistical methods to students in semiconductor engineering programs and related fields. It is intended for instructors who want to learn if and how JMP software meets the needs of their course or curriculum. Topics include:

• Identifying features in univariate and multidimensional data using interactive visualizations

• Quantifying the statistical evidence supporting a conclusion

• Monitoring process performance with statistical quality control methods

• Designing and analyzing experiments to find factors that most impact process variables

• Statistical and machine learning models for describing relationships and predicting outcomes