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A term which covers the large number of techniques for the analysis of the multivariate data which have in common the aim to assess whether or not the set of variables distinguish or discriminate between the two or more groups of the individuals. In medicine, for instance, this type of methods are generally applied to the problem of using optimally the results from the various tests or the observations of various symptoms to make the diagnosis which can only be confirmed perhaps by the post-mortem examination. In the two group case the mainly used method is Fisher's linear discriminant function, in which a linear function of variables giving the maximal separation between the groups is then determined. This results in the classification rule which may be used to assign the new patient to one of the two groups. The derivation of the linear function supposes that the variance-covariance matrices of the two groups are the same. If they are not then a quadratic discriminant function might be essential to distinguish between the groups. Such a function comprises of powers and cross-products of variables. The sample of the observations from which the discriminant function is derived is commonly known as the training set. When more than two groups are involved then it is possible to determine the several linear functions of the variables for separating them. In common the number of such functions which can be derived is the smaller of q and g-1 where q is the number of variables and g is the number of groups. The collection of the linear functions for discrimination is called as canonical discriminant functions or simply as canonical variates.
Chance events : According to the Cicero these are events which occurred or will occur in ways which are the uncertain-events which may happen, may not happen, or may happen in some
Paired samples are the two samples of the observations with the characteristic feature with each of the observation in one sample have only one matching observation in the other s
Paired availability design is a design which can lessen selection bias in the situations where it is not possible to use random allocation of the subjects to treatments. The desig
Generally the final stage of an exploratory factor analysis in which factors derived initially are transformed to build their interpretation simpler. Generally the target of the pr
Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing
#explanation of methods of collection of data..
The act of combining data from heterogeneous sources with the intent of extracting information that would not be available for any single source in isolation. An example is the com
a shop is selling laptops at regular price and at half price.If the laptops are regular price a day they will be at regular price tha day after with proba 2/3, if the laptops are a
Network sampling is a sampling design in which the simple random sample or strati?ed sample of the sampling units is made and all observational units which are linked to any of th
Biplots: It is the multivariate analogue of the scatter plots, which estimates the multivariate distribution of the sample in a few dimensions, typically two and superimpose on th
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