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.
To Learn more about factor analysis from the given link
brainly.com/question/26561565
#SPJ4
Answer:
EXPLINATION BELOW……
B
because B includes the midpoint and the top of the line
Answer:
<em>Any </em><em>4</em><em> </em><em>main</em><em> </em><em>nitrogenous</em><em> </em><em>excretory</em><em> </em><em>products</em><em> </em><em>are</em><em> </em><em>as</em><em> </em><em>follows:</em>
Explanation:
- Carbon dioxide
- Uric acid
- Urea
- ammonia, etc.
It is because liquids can move through it.
Don't open that link. Anyway, can you write the rest of the question? I'd be happy to help.
