Examples of using Two variables in English and their translations into Korean
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Colloquial
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Ecclesiastic
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Ecclesiastic
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Programming
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Computer
When you have two variables that are highly correlated, one might influence the other.
There are two variables in every DVI connector cable, and each represents one characteristic.
Positive relation means that two variables change in the same direction.
When adding two variables, it can be difficult to anticipate the result.
If we hold these two variables constant while analyzing our baseline data, we can observe that there are still variations in performance data.
If two variables are highly correlated,
Let's take the inverse, or when two variables vary inversely: this situation right over here.
The idea is simple: if you have two variables, the values in those variables are logically distinct.
According to our rules up here, they do have the same variables, and those two variables, x and y have the same power.
As you know, a line in the image space can be expressed with two variables.
We now have two variables, xand y, and both equal 5.
The whole process described above is a simile of what a computer can do with two variables.
In the case of education and political ideas, there are external factors that affect these two variables explaining part of their correlation.
If you want to analyze more than 32 values, and the values represent only one or two variables, you can use Data Tables.
The user might enter“Bob” and“Mary”, and adding those two variables together would be“BobMary”; which would make more sense.
At this point two variables have been defined and stored in the
We had two variables pointed at the same object behind the scenes. Let's look at a different kind of copying.
At the same time as he submitted to the Berlin Academy his own paper on cubic forms with two variables.
The correlation coefficient(a value between -1 and +1) tells you how strongly two variables are related to each other.
Second, in the relationship between the deep learning approach and organizational change readiness, LMX showed a moderating effect of strengthening the relationship between the two variables.