| 000 | 01883nam a2200361 a 4500 | ||
|---|---|---|---|
| 003 | EG-GiCUC | ||
| 005 | 20250223025949.0 | ||
| 008 | 091112s2009 ua d f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
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| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.03.01.M.Sc.2009.Do.O | ||
| 100 | 0 | _aDoaa Faik Madbuly | |
| 245 | 1 | 0 |
_aOn handling missing values in multivariate statistical process control via control charts / _cDoaa Faik Madbuly ; Supervised Nadia Makary , Sameer Sharawy , Mahmoud Alsaid |
| 246 | 1 | 5 | _aحول معالجة البيانات المفتقدة فى الضبط الاحصائى المتعدد للعمليات باستخدام خرائط التحكم |
| 260 |
_aCairo : _bDoaa Faik Madbuly , _c2009 |
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| 300 |
_a86P. : _bcharts ; _c25cm |
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| 502 | _aThesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics | ||
| 520 | _aControl charts are graphical tools widely used to monitor manufacturing process to quickly detect any change in a process that may result in a change in a produced quality . The most well known and widely used measure of the performance of the control chart is the average run length . The presence of missing values in a data set used in building the control chart technuque is a serious problem that may face the investigator when applying a control charts to practical situations | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aAverage run length and monte Carlo simulation | |
| 653 | 4 | _aMissing values | |
| 653 | 4 | _aMultivariate control chart | |
| 700 | 0 |
_aMahmoud Alsaid , _eSupervisor |
|
| 700 | 0 |
_aNadia Makary , _eSupervisor |
|
| 700 | 0 |
_aSameer Sharawy , _eSupervisor |
|
| 856 | _uhttp://172.23.153.220/th.pdf | ||
| 902 | _a1 | ||
| 905 |
_aFatma _eCataloger |
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| 905 |
_aNazla _eRevisor |
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| 942 |
_2ddc _cTH |
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| 999 |
_c24484 _d24484 |
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