This means that the data points lie perfectly on a line with negative slope.
For example, the points (0,4), (1,3), (2,2), (4,0) are perfectly correlated since they lie on the line y = -x + 4.
It is a negative correlation since the slope of the line is -1, a negative number, or alternatively because as x rises, y falls.
Negative
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.
Since y=14x is a perfect linear relation, the correlation would be 1.
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.
It is a measure of the extent to which a linear change in one quantity is accompanied by a linear change in the other quantity. Note that only linear changes are measured and that there is no causality.
A negative correlation is a measure of the linear component of a relationship where one variable increase as the other decrease.
The product-moment correlation coefficient or PMCC should have a value between -1 and 1. A positive value shows a positive linear correlation, and a negative value shows a negative linear correlation. At zero, there is no linear correlation, and the correlation becomes stronger as the value moves further from 0.
Negative
men and penises
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.
The correlation coefficient is a statistical measure that quantifies the strength and direction of a linear relationship between two variables. It ranges from -1 to 1, with -1 indicating a perfect negative correlation, 0 indicating no correlation, and 1 indicating a perfect positive correlation.
Since y=14x is a perfect linear relation, the correlation would be 1.
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.
A Pearson correlation measures the strength and direction of a linear relationship between two continuous variables, ranging from -1 (perfect negative correlation) to 1 (perfect positive correlation). An example could be studying the correlation between the amount of rainfall and crop yield in agricultural research to understand how variations in rainfall affect crop productivity.
False.
A negative correlation
It means that here is no linear relationship between the two variables. There may be a perfect non-linear relationship, though.