There can be. It depends on the variables.
A does but only if all of them are preceded by a decimal point.
Negative
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.
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.
It means that here is no linear relationship between the two variables. There may be a perfect non-linear relationship, though.
A does but only if all of them are preceded by a decimal point.
Scatter plot graphs are used in mathematics. They are used to show types of relationships or correlations that are between two sets of data.
Negative
It tells you how strong and what type of correlations two random variables or data values have. The coefficient is between -1 and 1. The value of 0 means no correlation, while -1 is a strong negative correlation and 1 is a strong positive correlation. Often a scatter plot is used to visualize this.
"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".
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.
No. Correlation studies cannot demonstrate ANY effects - positive or negative. They can only show that two (or more variables) move in the same or opposite dirctions. For example, my age is correlated with the number of cars on the road. But my age does not affect the number of cars, nor does the number of cars affect my age.
Line graph is used to show relationship between two variables.
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.
as one variable increases the other variable decreases