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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
Arithmetic Mean The process of computing Arithmetic Mean in the case of individual observations is to take the sum of the values of the variable and then divide by the number
Application of the chi Square Test
The 4 assumptions of regression: 1. Variables are normally distributed 2. Linear relationship between the independent and dependent variables 3. Homosced
Celia is a nurse in a geriatric ward. She noticed that older persons in her care are having problems sleeping at night. She decided to introduce non-pharmocologic ways of relaxat
Stratified Sampling Stratified Sampling is generally used when the population is heterogeneous. In this case, the population is first subdivided into several parts (or s
Main stages of Statistical Inquiry The following are the various stages of a statistical inquiry (1) Planning the Inquiry: First of all we have to assess the problem und
In PCA the eigknvalues must ultimately account for all of the variance. There is no probability,'no hypothesis, no test because strictly speaking PCA is not a statistical procedure
application of chi square test in civil engineering
We want to investigate the income data. In the Excel file Midterm Data.xls there is a tab labeled "Income Data 2006". The data in the tab is the income reported by 400 people in
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