If the correlation coefficient is 0, then the two tings vary separately. They are not related.
"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".
No. If the correlation coefficient is close to 1 or -1, then the two variables have a high degree of statistical linear correlation. See the related link, particularly the graphs which illustrate correlation.
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.
Correlation Coefficient.
If the correlation coefficient is 0, then the two tings vary separately. They are not related.
A correlation coefficient represents the strength and direction of the relationship between two variables. It measures how closely the two variables are related to each other.
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.
It is not possible to use correlation when the two variables are not related at all. the corelation coefficient value that will be obtained will have no significance.
partial correlation is the relation between two variable after controlling for other variables and multiple correlation is correlation between dependent and group of independent variables.
"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".
No. The units of the two variables in a correlation will not change the value of the correlation coefficient.
The weakest correlation coefficient is 0, which means there is absolutely no relationship between the two variables you are correlating.
The correlation coefficient is zero when there is no linear relationship between two variables, meaning they are not related in a linear fashion. This indicates that changes in one variable do not predict or explain changes in the other variable.
No. If the correlation coefficient is close to 1 or -1, then the two variables have a high degree of statistical linear correlation. See the related link, particularly the graphs which illustrate correlation.
The correlation coefficient for two variables is a measure of the degree to which the variables change together. The correlation coefficient ranges between -1 and +1. At +1, the two variables are in perfect agreement in the sense that any increase in one is matched by an increase in the other. An increase of twice as much in the first is accompanied by double the increase in the second. A correlation coefficient of -1 indicates that the two variables are in perfect opposition. The changes in the two variables are similar to when the correlation coefficient is +1, but this time an increase in one variable is accompanied by a decrease in the other. A correlation coefficient near 0 indicates that the two variables do not move in harmony. An increase in one is as likely to be accompanied by an increase in the other variable as a decrease. It is very very important to remember that a correlation coefficient does not indicate 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.