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Probability judgements: Human beings often require assessing the probability which some event will occur and accuracy of these probability judgements often determines success of our actions and our decisions. There is strong evidence that the human probability judgements are biased on the overestimation of low probabilities.
Jelinski Moranda model is t he model of software reliability which supposes that failures occur according to the Poisson process with a rate decreasing as more faults are diagnos
Line-intersect sampling is a technique of unequal probability sampling for selecting the sampling units in the geographical area. A sample of lines is drawn in a study area and, w
The procedures for extracting the pattern in a series of observations when this is obscured by the noise. Basically any such technique or method separates the original series into
Obuchowski and Rockette method is an alternative to the Dorfman-Berbaum-Metz technique for analyzing multiple reader receiver operating curve data. Instead of the modelling the ja
Markers of disease progression : Quantities which form a general monotonic series throughout the course of the disease and assist with its modelling. In uasual such quantities are
Auto correlation : The correlation of the internal observations in the time series, generally expressed as a function of the time lag between the observations. It is also used for
Ask questioThe finance manager of ‘Softy’ baby soap manufacturing company being successful in the first two years of the company’s operations is considering setting up another plan
Suppose that $4 million is available for investment in three projects. The probability distribution of the net present value earned from each project depends on how much is invest
Pattern recognition is a term for a technology that recognizes and analyses patterns automatically by machine and which has been used successfully in many areas of application inc
hello I have a dataset including both categorical & numerical variable for market segmentation.how can i cluster them via k-means in matlab? thank you
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