Resulting factors are called Second-order factors
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What is factor analysis?</h3>
- Factor analysis is a statistical approach for describing variability in seen, correlated variables in terms of a possibly smaller number of unobserved variables known as factors.
- It is possible, for example, that fluctuations in six known variables mostly reflect variations in two unseen (underlying) variables.
- Factor analysis looks for such joint fluctuations in response to latent variables that are not noticed.
- Factor analysis may be regarded of as a specific form of errors-in-variables models since the observed variables are described as linear combinations of the possible factors plus "error" terms.
- It may help to deal with data sets where there are large numbers of observed variables that are thought to reflect a smaller number of underlying/latent variables.
- It is one of the most commonly used inter-dependency techniques and is used when the relevant set of variables shows a systematic inter-dependence and the objective is to find out the latent factors that create a commonality.
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The awnser is b there is a mutation in the gene
The correct answer for the question that is being presented above is this one:
(1) viruses only: capsid, envelope with glycoproteins, capsomere (core protein)
<span>(2) host cell only: ribosome
</span><span>(3) both: DNA, RNA, Protein</span>
The way that I know it is that cells make up tissue, tissue makes up organs, and organs make up organ systems.
C is the answer to your problem
