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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Answer:
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Explanation:
<em><u>Our internal body temperature is regulated by a part of our brain called the hypothalamus. The hypothalamus checks our current temperature and compares it with the normal temperature of about 37°C. If our temperature is too low, the hypothalamus makes sure that the body generates and maintains heat.</u></em>
Lactic acid is a byproduct of short-term cellular respiration do to exercise, but if you mean lactose, then it's just the enzymes, that your stomach produces
Answer:GGATCGA
Explanation:
The complementary double helix of the DNA are antipararell to each other.
Chargaff's rule state that Adenine always pairs with thymine (double bond) and Cytosine always pairs with guanine (triple bond).
Therefore if a DNA molecule is CCTAGCT, then the sequence on the complementary strand of DNA will be GGATCGA as written below
5' CCTAGCT 3'
3' GGATCGA 5'