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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.
Difference between Correlation and Regression Analysis 1. Degree and Nature of Relationship: Coefficient of correlation measures the degree of covariance between two vari
Framing of Questionnaire: Questionnaire is a schedule of questions which is sent to the respondents for filling in by them in their own handwriting together the information rel
Let X 1 and X 2 be two independent populations with population means μ 1 and μ 2 respectively. Two samples are taken, one from each population, of sizes n 1 and n 2 re
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Apl.send me nots on hypothesis testing sk question #Minimum 100 words accepted#
construction of control chart,n chart
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Binomial Distribution Binomial distribution was discovered by swiss mathematician James Bernonulli, so this distribution is called as Bernoulli distribution also, this is a d
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