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
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<u>Answer:</u>
<em>When the volume is constant the pressure increases with temperature. </em>
<u>Explanation:</u>
<em>Gay Lussac’s law precisely explains the relation between pressure and temperature of a system which has constant volume.</em> In a system which has constant volume an increase in temperature indicates increase in temperature as well.
The reason behind the observation of this trend is the change in <em>randomness of particles of the system. </em>
With increase in temperature the particle movement becomes random and fast. <em>The particles hit the container walls at an increased rate and the pressure of the system increase. </em>
Explanation:
The first option, the others are normal
Answer:
If there are no animal cells, then life on earth would not exist. Also plants would dominate.
Explanation:
The red line is the wavelength
The blue line is the amplitude