A correlation coefficient of 1 or -1 would be the highest possible statistical relationship. However, the calculation of correlation coefficients between non independent values or small sets of data may show high coefficients when no relationship exists.
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.
A graph of Charles Law shows the relationship between temperature and volume of gas.
Any graph where, from left to right, the slope goes upward (assuming the axes are labelled in the standard way).
the p-value is used in statistics. It shows how strong the relationship between the variable are. Normally it is between -1 and 1. The closer it is to one the stronger the relationship is. the p-value is used in statistics. It shows how strong the relationship between the variable are. Normally it is between -1 and 1. The closer it is to one the stronger the relationship is.
it is called an inequality
If variables have zero correlation, they do not have a linear relationship. Zero correlation shows that two things were not found to be related.
No correlation.
that there is a correlation between the two variables. However, correlation does not imply causation, so it is important to further investigate to determine the nature of the relationship between the variables.
A correlation diagram visually represents the relationship between variables in a dataset. It shows how strongly and in what direction variables are related to each other.
correlation
If two variables are highly correlated, the Pearson correlation will be close to -1.0 or +1.0. A correlation of zero shows no relationship.
Trend correlation
D. Trend correlation
A scatterplot with no correlation means that there is no relation between the two categories, a negative correlation means that the two categories have a relationship that as one gets greater the other gets smaller
Multicolinearity shows the relationship of two or more variables in a multi-regression model. Auto-correlation shows the corellation between values of a process at different point in times.
correlation
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.