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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.
#regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
There are two types of drivers, high-risk drivers with an accident probability of 2=3 and low risk drivers with an accident probability of 1=3. In case of an accident the driver su
1 A penny is tossed 5 times. a. Find the chance that the 5th toss is a head b. Find the chance that the 5th toss is a head, given the first 4 are tails.
Your employer, Quick Hit Agency (QHA), is a debt collections agency. The company specializes in collecting small accounts. QHA does not deal in large accounts and does not take on
The cornlnunalities h j represent the fraction of the total variance' 'accounted for of variabie j. Ry calculating the communalities we can keep track of how much of-the orig
Exercise: (Binomial and Continuous Model.) Consider a binomial model of a risky asset with the parameters r = 0:06, u = 0:059, d = 0:0562, S0 = 100, T = 1, 4t = 1=12. Note that u
Correlation Analysis Correlation Analysis is performed to measure the degree of association between two variables. The measure is called coefficient of correlation. The coeffic
The incidence of occupational disease in an industry is such that the workers have a 20% chance of suffering from it. What is the probability that out of six workers 4 or more will
what is the aim of statistics?
I would like to know what the appropriate statistical test is for investigating an association between a nominal variable and an ordinal variable assuming normal distribution? It''
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