Derivation of the limits for control chart using the median absolute deviation for monitoring non-normal process

Journal of Mathematics and Statistics

Volumn 8, Issue 1, 2011, Pages 37-41

  Adekeye, K S ^a   Azubuike, P I ^a  

^a REDEEMER S UNIVERSITY   (Nigeria)

Author keywords

Cofta tablet; Control charts; Control limits interval; Manufacturing process; Median absolute deviation; Non normal; Process variability; Sigma approach; Soft drink; Standard deviation; Statistical process

Indexed keywords

EID: 84864137297     PISSN: 15493644     EISSN: None     Source Type: Journal    
DOI: 10.3844/jmssp.2012.37.41     Document Type: Article

References (10)

1. Abu-Shawiesh, M.O.A., 2008. A simple robust control chart based on MAD. J. Math. Stat., 4: 102-107. DOI: 10.3844/JMSSP.2008.102.107
2. Adekeye, K.S., 2009. An Introduction to Industrial Statistics (Concepts and Practice). Adewumi.
3. Hampel, F.R., 1974. The Influence curve and its role in Robust estimation. J. Am. Stat. Assoc. 69: 383-393. DOI: 10.2307/2285666
4. John, J.A., D. Whitaker and D.G. Johnson, 2006. Statistical Thinking in Business. 2nd Edn., Chapman and Hall/CRC, Boca Raton, ISBN: 1584884959, pp: 394.
5. Lax, D.A., 1985. Robust estimators of scale: Finitesample performance in long-tailed symmetric distributions. J. Am. Stat. Assoc., 80: 736-741. DOI: 10.2307/2288493
6. Montgomery, D.C., 2008. Introduction to Statistical Quality Control. 6th Edn., Wiley, Hoboken, N.J., ISBN: 0470169923, pp: 734.
7. Osanaiye, P.A., Adekeye, K.S. and Olugbara, O.O. 2001. Effect of normalizing statistical process control data using a developed johnson transformed-typed algorithm. J. Nigerian Stati. Assoc., 14: 34-51.
8. Shahriari, H., A. Maddahi and A.H. Shokouhi, 2009. A robust dispersion control chart based on Mestimate. J. Indus. Syst. Eng., 2: 297-307.
9. Shapiro, S.S. and M.B. Wilk, 1965. An analysis of variance test for normality (complete samples). Biometrika, 52: 591-611.
10. Simonoff, J.S., 1984. A comparison of robust methods and detection of outliers techniques when estimating a location parameter. Commun. Stat. Theory Meth., 13: 813-842. DOI: 10.1080/03610928408828722