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.
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
that would be Positive Correlation
Positive correlation.Positive correlation.Positive correlation.Positive correlation.
If Y increases as X increases, you are referring to a positive correlation. However, if Y falls as X increses, you have a negative 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
a correlation statement is a sentence that says whether the points on a scatterplot have a positive, negative or no correlation.ex. This graph shows a negative correlation, as the number of cows increases (x axis data) the profitability decreases (y axis data).
"If y tends to increase as x increases, then the data have a positive correlation. If y tends to decrease as x increases, then the data have a negative correlation. If the points show no correlation, then the data have approximately no correlation."
That's correct. The correlation between two suitable variables in a data set might be any value between -1 and 1, including 0.
that would be Positive Correlation
Positive correlation.Positive correlation.Positive correlation.Positive correlation.
If Y increases as X increases, you are referring to a positive correlation. However, if Y falls as X increses, you have a negative correlation.
Nothing, because they cannot. You need at least a pair of data for two variables before correlation can be calculated. That means at least four numbers.
A positive correlation is where the data has an increasing pattern. As X increases, Y also increases.
You can say that the correlation is positive if and only if the slope is positive. The correlation is zero if and only if the slope is zero. And the correlation is negative if and only if the slope is negative. On the other hand, slope does change when your measurement units change, while correlation does not change. (For example, the correlation between height in inches and weight in pounds will be the same as the correlation between height in centimeters and weight in kilograms, as long as both sets of measurements were taken on the same observations.)
You can find examples by typing it in to Google. Weak positive correlation is a set of points on a graph that are loosely set around the line of best fit. The line will be positive rising up from left to right. A weak correlation can vary a lot as long as you can decipher which direction the data tends towards you have a correlation. If the points are close to the line of best fit you have a strong correlation and with a set of points perfectly lined up is perfect correlation. All three types can positive negative or perfect.