Assume that you are correlating two variables x and y. If there is an increasing relationship between x and y, (that is , the graph of y=a+bx, slopes upward), the correlation coefficient is positive. Similarly, if there is a decreasing relationship, the correlation coefficient is negative. The correlation coefficient can assume values only between -1 and 1.
positive
That as one variable increases so does the other
the correlation coefficient range is -1 to +1
A positive correlation coefficient means that as the value of one variable increases, the value of the other variable increases; as one decreases the other decreases. A negative correlation coefficient indicates that as one variable increases, the other decreases, and vice-versa.
It means that the two variables are likely dependent. The higher the number of the positive correlation the stronger the connection.
No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).
Positive correlation = positive association Negative correlation = negative association
1.
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.
A correlation coefficient of 1 (r=1) is a perfect positive correlation.
positive
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.
The correlation coefficient, plus graphical methods to verify the validity of a linear relationship (which is what the correlation coefficient measures), and the appropriate tests of the statisitical significance of the correlation coefficient.
No, it depends upon the size of the coefficient of correlation: the closer to ±1 the stronger the correlation.When the correlation coefficient is positive, one variable increases as the other increases; when negative one increases as the other decreases.
The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).
This statement is incorrect. A correlation coefficient near 1 indicates a strong positive correlation between the variables, meaning that as one variable increases, the other tends to increase as well. Conversely, a correlation coefficient near -1 indicates a strong negative correlation, where one variable increases as the other decreases. A correlation coefficient close to 0 suggests little to no correlation.
Yes it can be a correlation coefficient.