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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Anaerobic condition refers to an environmental condition where oxygen is absent. In case of Electron Transport System (ETS) and ATP production, oxygen acts as the final acceptor of electrons. As oxygen is a reactant in ETS and ATP production, unavailability of oxygen can cause no oxidation of the coenzymes or the carriers such as NAPH and FADH2 and no ATP will be produced. Thus, both Electron Transport System and ATP production will stop in the absence of oxygen.
A lime? I don’t know what you are trying to rhyme?
