scholarly journals Outlier Diagnostic in Geodetic Intersection

2014 ◽  
Vol 10 (2) ◽  
pp. 61-65
Author(s):  
Jana Ižvoltová ◽  
Vladimír Koťka
Keyword(s):  
Hypothesis Testing ◽  
Outlier Detection ◽  
Detection Method ◽  
Extreme Values ◽  
Critical Value ◽  
Statistical Hypothesis ◽  
Statistical Hypothesis Testing ◽  
Intersection Method

Abstract Residuals are differences between observed and predicted variables. This paper describes outlier detection method with using studentized internal and external residuals, which was applied to find extreme values in dataset that comes from the planar intersection method. The detected outlier is analysed by the statistical hypothesis testing, where critical value is defined as a quantil of Studentized distribution.

Multiple Hypothesis Testing for Data Mining

2011 ◽  
pp. 1390-1395
Author(s):  
Sach Mukherjee
Keyword(s):  
Data Mining ◽  
Hypothesis Testing ◽  
Conventional Treatment ◽  
Statistical Significance ◽  
Multiple Hypothesis Testing ◽  
Statistical Hypothesis ◽  
Single Variable ◽  
Statistical Hypothesis Testing ◽  
Computationally Efficient ◽  
Error Probabilities

A number of important problems in data mining can be usefully addressed within the framework of statistical hypothesis testing. However, while the conventional treatment of statistical significance deals with error probabilities at the level of a single variable, practical data mining tasks tend to involve thousands, if not millions, of variables. This Chapter looks at some of the issues that arise in the application of hypothesis tests to multi-variable data mining problems, and describes two computationally efficient procedures by which these issues can be addressed.

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