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As one of the oldest multivariate statistical methods of data reduction, Principal Component Analysis (PCA)simplifies a dataset by producing a small number of derived variables that are uncorrelated and that account for most of the variation in the original data set. Eventually, the derived variables are combinations of the original variables. For example, it might be ?hat students take 10 examinations and some students do well in one exam whilst other students do better in another. It is difficult to compare one student with another when we have marks from 10 examinations to consider. One obvious way of comparing students is to calculate tlie mean score. This is a constructed combination of the existing variables,. However. we may get a more useful comparison of overall performances by considering other constructed combinations of the 10 exam marks. The PCA is one way of constructing such combinations, doing so in such ewakas to account for as much as possible of the variation in the original data. One can then compare students' performance by considering this much sn~aller number of variables.
Lifts usually have signs indicating their maximum capacity. Consider a sign in a lift that reads "maximum capacity 1400kg or 20 persons". Suppose that the weights of lift-users are
Prediction Inte rval We would like to construct a prediction interval around which would contain the actual Y. If n ≥ 30, ± Zs e would be the interval, where Z
Grid is the set of pairs {1, 2, 3, 4} x {1, 2, 3, 4}. Image is the power set of Grid. An element of Image is a subset of Grid and can be represented by a diagram on a 4 by 4
#question what is the statistical process to reduce hardness of water
Measurement of trend , least square method
Origin and Development of probability Theory: The credit for origin and development of probability goes to the European gamblers of 17 th century. They used to gamble on gam
f(x,y)=c(6-x-y) ,o find P(X+Y
Two students are sitting in a lecture and considering whether to ask a question from the professor (both of them are considering the same question). If they both ask, the questi
how can we graph a trend line by semiaverages and least square method?
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