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Q: Which value of r indicates a stronger correlation r equals 0.834 or r equals -0.925?

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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.

If the correlation coefficient is 0, then the two tings vary separately. They are not related.

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

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.

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.

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.

pH less than 7 indicates acid the lower the pH the stronger the acid. pH greater than 7 indicates alkalinity the higher pH the stronger the base.

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.

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.

1.

The neutral pH is 7,00.

The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).

No. The units of the two variables in a correlation will not change the value of the correlation coefficient.

Why the value of correlation coefficient is always between -1 and 1?

It will be invaluable if (when) you need to calculate sample correlation coefficient, but otherwise, it has pretty much no value.

A serious error. The maximum magnitude for a correlation coefficient is 1.The Correlation coefficient is lies between -1 to 1 if it is 0 mean there is no correlation between them. Here they are given less than -1 value so it is not a value of correlation coefficient.

Let me rephrase: Case 1: You have x and y variables, but the values for x is a constant (vertical line) Case 1: You have x and y variables, but the values for y is a constant (horizontal line) Result is that you have zero covariance, so a correlation coefficient can not be calculated because that would cause a division by zero. If one of your x value (Case 1) or y value (case 2) is not exactly the same as the others, then a correlation coefficient can be calculated, but does it mean anything? The correlation coefficient indicates a linear relationship between two random variables, not between a constant and a random variable.

correlation is drawn from all data points. if you look at the r^2 value and it's below 0.99 for example (should be higher in non research work (and in much research work) it indicates that 1 of your points may be an outlier. If you input all datapoints into excel, you may be able to see the point that's throwing it off. There are also statistical tests you can do to spot an outlier. In other words, correlation is not independent of an outlier. it will make the r^2 value worse. If the outlier is taken out, then the correlation could be deemed independent but only because you manipulated it and had taken the outlier out

Excel function indicates it is Sunday ie: =WEEKDAY("07/10/1990") returns value 1 which equals SUNDAY.

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