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Statistical analysis of ROC curves
Kutálek, David ; Bednář, Josef (referee) ; Michálek, Jaroslav (advisor)
The ROC (Receiver Operating Characteristic) curve is a projection of two different cumulative distribution functions F0 and F1. On axis are values 1-F0(c) and 1-F1(c). The c-parameter is a real number. This curve is useful to check quality of discriminant rule which classify an object to one of two classes. The criterion is a size of an area under the curve. To solve real problems we use point and interval estimation of ROC curves and statistical hypothesis tests about ROC curves.
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Introduction to Six Sigma Method and its Application for Process Improvements
Šimek, Petr ; Kutálek, David (referee) ; Bednář, Josef (advisor)
In this thesis I dealt with the Six Sigma method and uses in practice in Miele technica s.r.o. company. The first part deals with the theoretical description of Six Sigma, DMAIC methodology and used tools as SIPOC, Ishikawa diagram, Pareto diagram, or regression or correlation. The second part describes the application of Six Sigma methods, which I had the opportunity to perform as a team leader in the assembly process of washing machines and dryers.
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Introduction to Six Sigma Method and its Application for Process Improvements
Šimek, Petr ; Kutálek, David (referee) ; Bednář, Josef (advisor)
In this thesis I dealt with the Six Sigma method and uses in practice in Miele technica s.r.o. company. The first part deals with the theoretical description of Six Sigma, DMAIC methodology and used tools as SIPOC, Ishikawa diagram, Pareto diagram, or regression or correlation. The second part describes the application of Six Sigma methods, which I had the opportunity to perform as a team leader in the assembly process of washing machines and dryers.
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|
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Statistical analysis of ROC curves
Kutálek, David ; Bednář, Josef (referee) ; Michálek, Jaroslav (advisor)
The ROC (Receiver Operating Characteristic) curve is a projection of two different cumulative distribution functions F0 and F1. On axis are values 1-F0(c) and 1-F1(c). The c-parameter is a real number. This curve is useful to check quality of discriminant rule which classify an object to one of two classes. The criterion is a size of an area under the curve. To solve real problems we use point and interval estimation of ROC curves and statistical hypothesis tests about ROC curves.
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