The financial market influences personal corporate financial lives and the economic health of a country. Price change of stock market is not a completely random model. The pattern of financial market has been observed by some economists, statisticians and computer scientists. This paper gives a detailed idea about the sequence and state prediction of stock market using Hidden Markov Model and also making inferences regarding stock market trend. The one day difference in close value of stock market value has been used for some period and the corresponding transition probability matrix and emission probability matrix are obtained. Seven optimal hidden states and three sequences are generated using MATLAB and then compared.

Application of Statistical process control (SPC) is increasing being advocated in health science as a valuable quality improvement tool. The use of control charts in health science related applications differs somewhat from industrial. In SPC, cumulative sum (CUSUM) charts rather than Shewhart chart are used to detect smaller shifts in the process. In order to improve the detection capability relative to that of the Shewhart control charts, several control charts have been developed such as CUSUM charts, Exponentially weighted moving average(EWMA) charts and Sequential probability ratio test (SPRT) etc. Among them, the CUSUM charts are popular and effective. The CUSUM procedure has recently made its appearance in the field of medicine. The main purpose of this paper is to elucidate the common uses of CUSUM charts in healthcare and to describe different forms of CUSUM charts for monitoring performance over time when the outcome is related to health science.

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