Correlation determines relationship between two variables. For example changes in one variable influence another variable, we can say that there is a correlation between the two variables. For example, we can say that there exists a correlation between the number of hours spent on reading and preparation and the scores obtained in the examination. One can infer that higher the amount of time spent on preparation may result in better performance in examination leading to higher scores. Hence the above is a case of positive correlation. If an increase in independent variable leads to an increase in dependent variable, it is a case of positive correlation. On the other hand if an increase in independent variable leads to a reduction in dependent variable, it is a case of negative correlation. An example for negative correlation could be the relationship between the age advancement and resistance to diseases. As age advances, resistance to disease reduces.
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.
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.
positive
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
It's a negative correlation because it is less than 0
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.