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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.
limitations of time series analysis
Question: (a) (i) Define the term multicollinearity. (ii) Explain why it is important to guard against multicollinearity. (b) (i) Sometimes we encounter missing values
Each question, by default, should be solved INDIVIDUALLY, unless marked as \collaborative". Questions marked as \collaborative" implies that for those questions you are encourage
Assumptions in ANOVA The various populations from which the samples are drawn should be normal and have the same variance. The requirement of normality can be discarded if t
Scenario: Many of the years 5 and year 6 learners' at Woodlands Park School were excited about being chosen for the cross-country team. Every day, they were able to run laps of t
how can i use continuous frailty in multi state models?
The regression line should be drawn on the scatter diagram in such a way that when the squared values of the vertical distance from each plotted point to the line are added, the to
An approximation to the error of a Riemannian sum: where V g (a; b) is the total variation of g on [a, b] dened by the sup over all partitions on [a, b], including (a; b
Meaning and Definitions of Regression The dictionary meaning of regression is just opposite the meaning of progression. Progression means to move forward while regression means
Accident proneness A personal psychological issue which affects the individual's probability of suffering the accident. The concept has been studied statistically under the num
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