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A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how to conduct the statistical aspects of an experiment and which action to take for each possible outcome. Choosing the decision function needs a loss function to be defined which assigns numerical values to making bad or good decisions. Explicitly a general loss function is denoted by L d; expressing how bad it would be to make decision d if the parameter value were. A quadratic loss function, it could be defined as and a bilinear loss function as
Computer-aided diagnosis : The computer programs which are designed to support clinical decision making. In common, such systems are based on the repeated application of the Bay
High-dimensional data : This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21 st
Bivariate boxplot : A bivariate analogue of boxplot in which the inner area contains 50%of the data, and a 'fence' helps to identify the potential outliers. Robust methods or techn
Path analysis is a device for evaluating the interrelationships among the variables by analyzing their correlational structure. The relationships between the variables are man
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
Difference b/w historigram and histogram
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
Conjoint analysis : The method used basically in market research which is similar in many respects to the various dimensional scaling. The method attempts to assign values to the l
Multivariate data is the data for which each observation consists of the values for more than one random variable. For instance, measurements on the blood pressure, temperature an
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
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