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Statistics in Semiconductor Test: Going beyond Yield
September/October 2009 (vol. 26 no. 5)
pp. 64-73
W. Robert Daasch, Portland State University
C. Glenn Shirley, Portland State University
Amit Nahar, Texas Instruments

Editor's note:

The quantity and complexity of data generated at each test manufacturing step can be daunting. This article, which emerged from a tutorial presented at ITC 2008, explains the application of statistics to help process that data and provides examples of how test has shifted from descriptive to predictive methods.

—Nur A. Touba, University of Texas

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Index Terms:
statistical test, design and test, statistical modeling, multisite testing, burn-in, outlier identification, outlier screening, data mining
W. Robert Daasch, C. Glenn Shirley, Amit Nahar, "Statistics in Semiconductor Test: Going beyond Yield," IEEE Design & Test of Computers, vol. 26, no. 5, pp. 64-73, Sept.-Oct. 2009, doi:10.1109/MDT.2009.123
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