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The phrase first spoken by one of the witches in Macbeth. Now this is used to describe the exponential rise in the number of possible locations in the multivariate space as dimensionality increases. Thus the single binary variable has the two probable values, a 10-dimensional binary vector has over the thousand possible values and a 20-dimensional binary vector over the million possible values. This implies that sample sizes should be increase exponentially with the dimension in order to maintain the constant average sample size in the cells of space. Another consequence is that, for the multivariate normal distribution, the vast mass of the probability lies far from the centre of it if the dimensionality is large.
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
Monty Hall problem : A apparently counter-intuitive problem in the probability which gets its name from the TV game show, 'Let's Make a Deal' hosted by the Monty Hall. On show a pa
Influence statistics: The range of statistics designed to assess the effect or the in?uence of an observation in determining results of the regression analysis. The general approa
Economic Interpretation of the Optimum Simplex solution
A rule for computing the number of classes to use while constructing a histogram and can be given by here n is the sample size and ^ γ is the estimate of kurtosis.
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
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Coincidences : Astonishing concurrence of the events, perceived as meaningfully related, with no apparent causal connection. Such type of events abounds in everyday life and is oft
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
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
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