Resulting factors are called Second-order factors
<h3>
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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<span>a. he was born in 1707 and died in 1778.</span>
Ans.
Genetic codes provide information for the protein synthesis as each code specifically codes a particular amino acid that gets joined in polypeptide chain during the process of translation.
Each genetic code is three letter code, made up of three nitrogenous bases. There are four different bases in DNA or RNA that make sixty four codes with different combinations, out of which sixty one code for amino acids and three act as stop codons.
Thus, nitrogenous bases are important in preserving the genetic codes.
It is thought that life arose on earth around four billion years ago. The endosymbiotic theory states that some of the organelles in today's eukaryotic cells were once prokaryotic microbes.
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