Q: Is -.187 a positive or negative correlation?

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Positive correlation has a positive slope and negative correlation has a negative slope.

A positive correlation.

Positive correlation = the slope of the scattered dots will rise from left to right (positive slope) Negative correlation = the slope of the scattered dots will fall from left to right (negative slope) No correlation = no real visible slope, the dots are too scattered to tell.

They can be positive correlation, negative correlation or no correlation depending on 'line of best fit'

No, it indicates an extremely strong positive correlation.

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Positive correlation has a positive slope and negative correlation has a negative slope.

Positive correlation = positive association Negative correlation = negative association

A positive correlation.

positive correlation-negative correlation and no correlation

I believe you are asking how to identify a positive or negative correlation between two variables, for which you have data. I'll call these variables x and y. Of course, you can always calculate the correlation coefficient, but you can see the correlation from a graph. An x-y graph that shows a positive trend (slope positive) indicates a positive correlation. An x-y graph that shows a negative trend (slope negative) indicates a negative correlation.

Positive correlation = the slope of the scattered dots will rise from left to right (positive slope) Negative correlation = the slope of the scattered dots will fall from left to right (negative slope) No correlation = no real visible slope, the dots are too scattered to tell.

They can be positive correlation, negative correlation or no correlation depending on 'line of best fit'

No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).

no correlation.

a correlation on a graph is when the line of best fit is positive, negative or none.

If the data have a positive or negative correlation, it means the data have a linear relationship in the form of an equation of a line; or Y = mX + b.

If the two variables increase together and decrease together AND in a linear fashion, the correlation is positive. If one increases when the other decreases, again, in a linear fashion, the correlation is negative.