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The analysis of data which are the functions observed continuously, for instance, functions of time. Basically a collection of statistical techniques or methods for answering questions like 'in what manner do the curves in the sample differ?', using information on the curves like slopes and curvature.
A mixture of benzene, toluene, and xylene enters a two-stage distillation process where some of the componentsare recovered. The distillation process operates at steady-state condi
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
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
Pie chart is an extensively used graphical technique for presenting relative frequencies related with the observed values of the categorical variable. The chart comprises of a cir
Convex hull trimming : A procedure which can be applied to the set of bivariate data to permit robust estimation of the Pearson's product moment correlation coef?cient. The points
Mortality odds ratio is the ratio equivalent to the odds ratio used in case-control studies where the equivalent of the cases are deaths from the cause of interest and the equival
Attitude scaling : The process of analysing the positions of the individuals on scales purporting to measure attitudes, for instance a liberal-conservative scale, ora risk-willingn
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent
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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