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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 21st century\ such data sets are collected in number of areas, such as, text/web data mining and bioinformatics. The job of extracting meaningful statistical and biological information from such data sets present many challenges for which a number of recent methodological developments, for instance, sure screening methods, lasso, and Dantzig selector, might be quite helpful.
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
Growth curve analysis is t he general term for methods dealing with development of the individuals over time. A classic instance includes recordings made on a group of children, sa
The objective of this assignment is to test your understanding in the learning outcome (LO2) and learning outcome (LO3) and learning outcome (LO4). 1) This is a grouped assignme
This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea o
The method of displaying the geographical variability of the disease on maps using different colors, shading, etc. The logic is not new, but the arrival of computers and computer g
Negative binomial distribution is the probability distribution of number of failures, X, before the kth success in the sequence of Bernoulli trials where the probability of succes
#explanation of methods of collection of data..
Cause specific death rate : A death rate calculated for the people dying from the specific disease. For instance, the below given are the rates per 1000 people for three disease cl
Inliers is the term used for the observations most likely to be subject to error in situations where the dichotomy is developed by making a ‘cut’ on an ordered scale, and where th
VIF is the abbreviation of variance inflation factor which is a measure of the amount of multicollinearity that exists in a set of multiple regression variables. *The VIF value
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