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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Most becomes carbon dioxide and the rest of it often becomes fossil fuels such as coal
Every organism’s DNA will not look and act the exact same way. If the parent reproduces asexually is the only exception to that rule. However, if all organism’s DNA resembled and acted as a deer’s DNA, then all organisms would be deer. Therefore, there are genetic differences that separate species and ensure different behaviors from organism to organism. While the DNA will be similar by using the same four nucleic bases, there is an entirely different combination of those bases from organism to organism.
Answer:
The cell membrane is permeable to small solutes to let them easily diffuse in and out of the cells.
