A positive correlation between two variables, say X and Y, means that if one increases, the other will too. No correlation means that they are not related. A negative correlation means that as one increases, the other decreases.
Normally you will see this in studies as "Recent studies demonstrated a positive correlation between eating too much and obesity."
Or, "recent studies demonstrate a negative correlation between a healthy, balanced diet and obesity".
Negative
Correlation is a statistical measure of the linear association between two variables. It is important to remember that correlation does not mean causation and also that the absence of correlation does not mean the two variables are unrelated.
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.
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.
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.
It mean that there is no correlation between the two variables. The variables are the same.
Negative
Correlation is a statistical measure of the linear association between two variables. It is important to remember that correlation does not mean causation and also that the absence of correlation does not mean the two variables are unrelated.
A positive correlation between two variables means that there is a direct correlation between the variables. As one variable increases, the other variable will also increase.
"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".
Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.
A negative correlation means that two variables are inversely related. This means that as one variable increases the other decreases. When a negative correlation is plotted, it forms a downward slanting line.
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.
I think you're referring to Correlation. This means the relationship between two variables. There can be a positive correlation, where as one variable increases, so does the other. There can be a negative correlation, where as one variable increases, the other decreases. Lastly, there can be no correlation, where there is no relationship between the two variables.
as one variable increases the other variable decreases
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.
Correlation coefficient is a measure of the strength and direction of a relationship between two variables. It quantifies how closely the two variables are related and ranges from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no correlation.