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Q: When two variables are empirically correlated with each other they must?

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A correlation coefficient of zero means that two things are not correlated to each other.

There is multicollinearity in regression when the variables are highly correlated to each other. For example, if you have seven variables and three of them have high correlation, then you can just use one them in your dependent variable rather than using all three of them at the same time. Including multicollinear variables will give you a misleading result since it will inflate your mean square error making your F-value significant, even though it may not be significant.

If two things correlate or are correlated , they are closely connected or strongly influence each other. correlation-noun

Some times. At other times it uses mutually dependent variables (changes in each variable affect the other).

Two or more explanatory variables are collinear when they have a linear relationship with each other. You are usually expected to remove at least one of the variables from your multiple regression analysis.

Related questions

The preposition "with" should follow the word "correlated." For example: "The data suggests that these two variables are strongly correlated with each other."

If two graphs have exactly the same shape, it indicates that the variables are proportional to each other. This means that as one variable increases or decreases, the other variable changes in a consistent and fixed ratio.

Correlate is two things that are closely connected. It is also correlated with each other.

Usually it means that each of the variables is dependent on the other. if one changes, so does the other.

A correlation coefficient of zero means that two things are not correlated to each other.

There is multicollinearity in regression when the variables are highly correlated to each other. For example, if you have seven variables and three of them have high correlation, then you can just use one them in your dependent variable rather than using all three of them at the same time. Including multicollinear variables will give you a misleading result since it will inflate your mean square error making your F-value significant, even though it may not be significant.

If two things correlate or are correlated , they are closely connected or strongly influence each other. correlation-noun

There are infinitely many possible ways in which two variables can be related to one another.

Some times. At other times it uses mutually dependent variables (changes in each variable affect the other).

It means there is no discernable relationship between the two variables. Knowing one variable does not give you any help in working out the other. They are independent of each other.

Yes. They are inversely proportional. The proportion y ∝ 1/x, means xy=K, where K is the constant.

Two or more explanatory variables are collinear when they have a linear relationship with each other. You are usually expected to remove at least one of the variables from your multiple regression analysis.