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A term commonly encountered in the application of the agglomerative hierarchical clustering techniques, where it refers to the 'tree-like' diagram illustrating the series of steps taken by the process in proceeding from n single member 'clusters' to a single group comprising all n individuals. The instance shown in the figure arises from applying single linkage clustering to the following matrix of the Euclidean distances between five points:
Conditional logistic regression : The form of logistic regression designed to work with the clustered data, such as data including matched pairs of the subjects, in which subject-s
Chebyshev's inequality: A statement about the proportion of the observations which fall within some number of the standard deviations of the mean for any of the probability distri
The procedure in which initially the sample of subjects is selected for generating the auxillary information only, and then the second sample is selected in which the variable of i
This term sometimes used to describe the extra factor in variance of the sample mean when n sample values are drawn without the replacement from the finite population of size N. Th
Input to the compress is a text le with arbitrary size, but for this assignment we will assume that the data structure of the file fits in the main memory of a computer. Output of
The special cases of the probability distributions in which the random variable's distribution is concentrated at one point only. For instance, a discrete uniform distribution when
Question 1 A box contains 20 fuses of which 5 are defective If 2 fuses are chosen together at random what is the probability that both the fuses are defective? Question 2 A c
Barrett and Marshall Model for conception : A biologically reasonable model for the probability of conception in a particular menstrual cycle, which supposes that the batches of sp
i have an assignment for experimental design which is must done by SAS program can you help me also i need to hand in the assignment till thursday shall i send it for you ?
How to estimate MLE for statistical anslysis using Markov Model?
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