<span> overvalue their physical appearance, weight, and body shape. </span>
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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The correct answer is: Glycogen phosphorylase would remain phosphorylated and retain some activity.
Glycogen phosphorylase is directly involved in the regulation of glucose levels since it is a glucose sensor in liver cells: when glucose levels are low, phosphorylase is active and it has PP1 bound to it (phosphatase activity of PP1 is prevented). Therefore, there phosphorylase a will accelerate glycogen breakdown.
Answer:
Becuase in canada here it snows and yeah.
Explanation:
Fluid shift from vascular to interstitial can cause the water in blood is decreased, causing the other component level in blood seems to be increased(hemoconcentration).
In this case, hematocrit is one of the marker in laboratory that can be used for assessing hemoconcentration.
