r = -0.925 is stronger.
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 observed relationship indicates that the a one-to-one correspondence exists between the variables of interest. In effect, the value of the obtained r-value is -1 or 1.
A correlation exists in a scatter plot if there is a general trend in the outputs as inputs increase. If the outputs generally increase in value, then there is a positive correlation. If the outputs generally decrease in value, then there is a negative correlation.
The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).
-1 to 1
A positive value for a correlation indicates a positive correlation; e.g. it has a positive slope.
Any value between 0.40 and 1 or any value between -1 and -0.40.
A correlation reflects the strength of the relationship between two variables. A correlation doesn't reflect causation, but merely that two phenomena are present at the same time. The closer the value is to 1, the stronger the relationship between two variables is. This value can be positive or negative. A negative value merely indicates that, as the values on one variable increase, the values on the second variable decrease. A positive correlation indicates that both values will increase or decrease together.
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 stronger correlation will be the one whose absolute value is closest to one. For example, r = -.78 is stronger than r=.65, because: |r| = |-.78| = .78 > |r| = |.65| = .65
If the correlation coefficient is 0, then the two tings vary separately. They are not related.
The correlation coefficient ranges from 0 to ±1. The sign of the correlation coefficient shows the correlation as positive (as one increases so does the other) or negative (as one increases the other decreases). 0 represent no correlation and ±1 represents perfect correlation. The further from 0 towards ±1, the stronger the correlation, ie the greater the absolute value* of the correlation coefficient the stronger the correlation. To have a stronger correlation than -0.54 the absolute value must be greater than 0.54; ie all correlation coefficients that are less than -0.54 (eg -0.6, -0.9) and all those greater than +0.54 (eg 0.7, 0.95) are stronger correlations. Mathematically speaking, all those with a correlation coefficient r such that |r| > 0.54 *The absolute value of a number is the number ignoring its sign (ie how far it is away from 0 ignoring the direction along the number line), eg |56| = 56 |-45| = 45 |-56| = 56 Thus |-56| = |56| = 56.
The further the correlation coefficient is from 0 (ie the closer to ±1) the stronger the correlation.Therefore -0.75 is a stronger correlation than 0.25The strength of the correlation is dependant on the absolute value of the correlation coefficient; the sign of the correlation coefficient gives the "relative" slope of correlation line:+ve (0 to +1) means that as one variable increases the other also increases;-ve (0 to -1) means that as one variable increases the other decreases.
The observed relationship indicates that the a one-to-one correspondence exists between the variables of interest. In effect, the value of the obtained r-value is -1 or 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.
Assuming that all of these coefficients are based on samples of the same size then the weakest correlation is -0.01 because its absolute value (0.01) is the smallest.
An inequality (or an inequity) is when an equation has either of the symbols < or > in place of the equals sign. < indicates that the value to the left of it is less than the value to the right of it. > indicates that the value to the left of it is greater than the value to the right of it. Two other signs are also used: ≤ and ≥ ≤ indicates that the value to the left of it is "less than or equal to" the value to the right of it. ≥ indicates that the value to the left of it is "greater than or equal to" the value to the right of it.