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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. The PCA is merely a mathematical manipulation to recast m variables as m factors. Factor analysis (FA), however, brings a priori knowledge to the problem solving exercise.
'There is a short list of primary assumptions behind factor analysis. But basically. factor analysis assumes that there are cowelations/covariances between the m variables in the datp set that are a result of p underlying, mutually uncorrelated factors.
There are situations where none of the three averages is fully satisfactory. For example, if the number of items in a series is very small, none of these av
(a) If one solves the ordinary differential equation using Euler's method find an expression for the local truncation error. (b) Using the result of (a) above what will
Meaning and Definitions of Business Forecasting The problem of business forecasting refers to the analysis of the past and present economic conditions. With the objectiv
Define sampling unit and population for selecting a random sample in every case. a) 100 voters from a constituency b) 20 stocks of National Stock Exchange c) 50 account ho
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Consider the sample of 60 package design ratings given in the table below. A Sample of Package Design Ratings (Composite S
entropy test to measure interaction between enviornmental factors and genes
Two individuals, player 1 and player 2, are competing in an auction to obtain a valuable object. Each player bids in a sealed envelope, without knowing the bid of the other player
The PCA is amongst the oldest of the multivariate statistical methods of data reduction. It is a technique for simplifying a dataset, by reducing multidimensional datasets to lower
how to analyzePractice-Based Evidence Back to the Future
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