Between -1 and 0.
Correlation Coefficient.
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.
Correlation is a measure of association between two variables and the variables are not designated as dependent or independent. Simple regression is used to examine the relationship between one dependent and one independent variable. It goes beyond correlation by adding prediction capabilities.
A coefficient of zero means there is no correlation between two variables. A coefficient of -1 indicates strong negative correlation, while +1 suggests strong positive correlation.
It mean that there is no correlation between the two variables. The variables are the same.
Correlation Coefficient.
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.
negative correlation
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".
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.
Correlation coefficients measure the strength and direction of a relationship between two variables. They range from -1 to 1: a value of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation. They are commonly used in statistics to quantify the relationship between variables.
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.
Correlation is a measure of association between two variables and the variables are not designated as dependent or independent. Simple regression is used to examine the relationship between one dependent and one independent variable. It goes beyond correlation by adding prediction capabilities.
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.
Chance association, (the relationship is due to chance) or causative association (one variable causes the other).
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 coefficient of zero means there is no correlation between two variables. A coefficient of -1 indicates strong negative correlation, while +1 suggests strong positive correlation.