Quality information is an organized set of relevant data that can be used for various purposes.
Quality information is made up of a group of data already supervised and ordered, which serve to build a message based on a certain phenomenon or entity.
- It allows solving problems and making decisions, since its rational use is the basis of knowledge.
- It is a resource that gives meaning to reality, through codes and data sets.
Therefore, we can conclude that quality information is the set of data, already processed and ordered for understanding, that provide new knowledge that can be used for different purposes.
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The relationship that exists between a homogeneous mixture and the number of phases in the mixture is one phase.
Given that there is a relationship exists between a homogeneous mixture and the number of phases in the mixture.
We are required to tell the name of the relationship that exists between a homogenous mixture and the number of phases in the mixture.
A homogeneous mixture is basically a gaseous, liquid or solid mixture that has the same proportions of its components throughout a given sample.
The name of the relationship is one phase.
A phase is basically a relationship between the cycles of different periodic waves.
Hence the relationship that exists between a homogeneous mixture and the number of phases in the mixture is one phase.
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Drawing a conclusion from the graph, the true statement from the option given is <em>Voter turnout in national election years is irregular from 2006 to </em><em>2020</em><em>.</em><em> </em>
Voter turnout in 2006 was 40% while in 2014 it was 35% `; hence, voters were more interested in 2006 than in 2014.
In some of the years given, less than 50% of Americans participated in the polls.
Hence, the true statement is <em>"</em><em>Voter turnout in national election years is irregular from 2006 to </em><em>2020</em><em>"</em><em> </em>
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Answer:
The United States has a trade deficit with China
Explanation:
Edg2020
The formula for Sums of squares of the residuals (SSR) is attached below.
Therefore, option B is correct:
B. I would calculate the difference between the observed outcome (Y) and the predicted value of Y (Y_hat), square each one of these differences, and add them up.
