Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to identify statistical outliers in test data for components, including local outliers representing outliers within subsets of larger data populations.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a fabrication process for components based on test data for the components.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically select one or more outlier identification algorithms for identifying statistical outliers in test data for components.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a component fabrication process guided by characteristics of the test data for the components.

Abstract: A method and apparatus for testing semiconductors according to various aspects of the present invention comprises a test system comprising composite data analysis element configured to analyze data from more than one dataset. The test system may be configured to provide the data in an output report. The composite data analysis element suitably performs a spatial analysis to identify patterns and irregularities in the composite data set. The composite data analysis element may also operate in conjunction with a various other analysis systems, such as a cluster detection system and an exclusion system, to refine the composite data analysis. The composite may also be merged into other data.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically select one or more outlier identification algorithms for identifying statistical outliers in test data for components.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically select one or more outlier identification algorithms for identifying statistical outliers in test data for components.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a fabrication process for components based on test data for the components.

Abstract: A method and apparatus for testing semiconductors according to various aspects of the present invention comprises a test system comprising composite data analysis element configured to analyze data from more than one dataset. The test system may be configured to provide the data in an output report. The composite data analysis element suitably performs a spatial analysis to identify patterns and irregularities in the composite data set. The composite data analysis element may also operate in conjunction with a various other analysis systems, such as a cluster detection system and an exclusion system, to refine the composite data analysis. The composite may also be merged into other data.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically select one or more outlier identification algorithms for identifying statistical outliers in test data for components.

Abstract: A method and apparatus for testing semiconductors according to various aspects of the present invention comprises a test system comprising an outlier identification element configured to identify significant data in a set of test results. The test system may be configured to provide the data in an output report. The outlier identification element suitably performs the analysis at run time. The outlier identification element may also operate in conjunction with a smoothing system to smooth the data and identify trends and departures from test result norms.

Abstract: A method and apparatus for smoothing data comprises adjusting data according to a first smoothing technique and selectively adjusting the data according to a second smoothing technique. The method and apparatus applies a first smoothing technique to a selected datum to adjust a value. The method and apparatus also compares preceding adjusted data to preceding raw data to generate a comparison result and may apply a second smoothing technique to the selected datum according to whether the comparison result meets a threshold. In addition, the method and apparatus of various embodiments may calculate a predicted value of the selected datum and apply another smoothing technique to the selected datum according to whether the predicted value meets a second threshold.

Abstract: A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a fabrication process for components based on test data for the components.

Abstract: A method and apparatus for testing semiconductors according to various aspects of the present invention comprises a test system comprising composite data analysis element configured to analyze data from more than one dataset. The test system may be configured to provide the data in an output report. The composite data analysis element suitably performs a spatial analysis to identify patterns and irregularities in the composite data set. The composite data analysis element may also operate in conjunction with a various other analysis systems, such as a cluster detection system and an exclusion system, to refine the composite data analysis. The composite may also be merged into other data.

Abstract: A method and apparatus for testing semiconductors according to various aspects of the present invention comprises a test system comprising an outlier identification element configured to identify significant data in a set of test results. The test system may be configured to provide the data in an output report. The outlier identification element suitably performs the analysis at run time. The outlier identification element may also operate in conjunction with a smoothing system to smooth the data and identify trends and departures from test result norms.

Abstract: A method and apparatus for smoothing data according to various aspects of the present invention comprises adjusting data according to a first smoothing technique and selectively adjusting the data according to a second smoothing technique. In one embodiment, the method and apparatus applies a first smoothing technique to a selected datum to adjust a value. The method and apparatus also compares preceding adjusted data to preceding raw data to generate a comparison result and may apply a second smoothing technique to the selected datum according to whether the comparison result meets a threshold. In addition, the method and apparatus of various embodiments may calculate a predicted value of the selected datum and apply another smoothing technique to the selected datum according to whether the predicted value meets a second threshold.