Faculty of Pharmacy, Cairo University, Egypt.
Research Article
World Journal of Advanced Research and Reviews, 2019, 01(01), 039-048.
Article DOI: 10.30574/wjarr.2019.1.1.0013
Received on 21 January 2019; revised on 16 February 2019; accepted on 21 February 2019
Control charts are a valuable assessment tool in the healthcare industry. The ease of use of these trending charts is crucial to obtain timely important results with minimum time and efforts. The current case showed analysis of non-normal data to obtain control charts with useful output without using exhaustive different means of transformation and/or omitting aberrant numbers. Raw results for the quality of purified water from water treatment plant that converts municipal water to purified water were collected from two points-of-use - (ζ and Ψ). Data gathered were conductivity and total organic carbon (TOC) measurements. The statistical processing and control charts were done using commercial statistical software package. Statistical analysis of data showed that conductivity and TOC results of both points did not follow Gaussian distribution except TOC of point Ψ where it passed normality test, but they were closest to other distributions. There were several observations of outlier values from the results. Moreover, data normalization did not improve after removal of the extreme values. Data were switched to be interpreted using Laney-modified attribute control charts and compared with the original results drawn using individual-moving range (I-MR). Interestingly, both types of control charts agreed regarding control limits and some alarm points. I-MR and Laney-attribute charts could be used for non-normal data with unusual other types of distributions that may not be suitable for conventional types of control charts with the variable charts possess greater sensitivity of alarm detection over the attribute charts.
Conductivity; Total organic carbon; I-MR; Laney-attribute; Normalization; Purified water
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Eissa Mostafa. Application of control charts for non-normally distributed data using statistical software program: A technical case study. World Journal of Advanced Research and Reviews, 2019, 1(1), 0-0. Article DOI: https://doi.org/10.30574/wjarr.2019.1.1.0013