Assertion: correlation | /r/HasProperty | equal
Facets:
value: always
type: DEGREE
value: to zero
type: OTHER
value: to 0
type: OTHER
value: to the covariance
type: OTHER
value: across groups
type: OTHER
value: in the population
type: OTHER
value: for males
type: OTHER
value: for females
type: OTHER
Source sentences:
text: There is no reason to print both triangles because the two triangles of a correlation matrix are always mirror images of each other (the correlation of variable x with variable y is always equal to the correlation of variable y with variable x).
text: Sometimes we shall use subscripts to clarify which correlation coefficient we are talking about: The symbol r XY denotes the correlation coefficient for X and Y. The correlation coefficient for a scatterplot of Y versus X is always equal to the correlation coefficient for a scatterplot of X versus Y (r XY = r YX ).
text: Note that this says the correlation between 1 and 3 is equal to the beta for 3 from 1 plus the regression for 3 from 2 times the correlation between 1 and 2.
text: We can also test whether the correlations are equal across groups (e.g., whether the correlation between SAT-V and GPA is equal for males and females).
text: We can also test whether the correlations are equal across groups (e.g., whether the correlation between SAT-V and GPA is equal for males and females).
text: For example, we could test whether the correlation between SAT and GPA is equal across all the state universities in Florida.
text: Suppose you want to test whether two correlations taken from the same sample are equal, that is, you want to test the equality of two elements from the same correlation matrix.
text: An example of the first type would be a test of whether the correlation between cognitive ability scores and performance in a class on U.S. history is equal to the correlation between cognitive ability scores and performance in a class on psychology.
text: An example of the latter would be whether the correlation between scores on a cognitive ability test and performance on a class test in psychology is equal to the correlation between personality test scores and scores on an interview used to determine a person's suitability for personal counseling as a therapist (whew, what a long sentence).
text: We can therefore reject the null that the correlations are equal in the population.
text: This says that the correlation between observed (measured) variables is equal to the correlation between their true scores, that is, the scores that would be observed with no error times the square root of the product of the two reliabilities, one reliability for each variable.
text: We can show that the correlation between two features is in fact equal to the covariance of two standardized features.
text: A correlation coefficient that is equal to 0 demonstrates the weakest possible linear relationship between the components being examined.
text: The correlation coefficient is equal to the covariance divided by the product of the standard deviations of the variables.
text: If the correlation coefficient is equal to zero, there is no linear relation between x and y. however, this does not necessarily mean that there is no relation at all between the two variables.