Q: A positive value for a correlation indicates?

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No, it indicates an extremely strong positive 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.

POSITIVE CORRELATION IS CORRELATION THAT IS LINKED. REPHRAISED IT MEANS:POSITIVE CORRELATION IS CORRELATION IN WHICH BOTH AXIS ARE LINKED. SO IN SOME EXTREME CASES IT WOULD BE, (X=Y).BUT ON WITH THE QUESTION ANSWERING.HERE ARE A FEW EXAMPLES OF POSITIVE CORRELATION:1. THE AMOUNT OF COFFEE DRUNK AND THE NUMBER OF HOURS STAYED AWAKE.2. THE NUMBER OF PEOPLE FLYING TO AUSTRALIA AND THE NUMBER OF PLANES FLYING TO AUSTRALIA.THESE CAN EASILY BE CHANGED INTO SCATTER DIAGRAMS. IF YOU WANT TO KNOW MORE ABOUT POSITIVE CORRELATION THAN COME TO HAWLEY PLACE SCHOOL nd ask to see mr freeman.OTHER EXAMPLES OF POSITIVE CORRELATION IS THAT1.MARKS OF STUDENT AND HIS QUOTIENT. IN THIS CASE THERE IS POSITIVE CORRELATION BETWEEN THESE TWO VARIABLE.ON OTHER HAND IN SOME OTHER SITUATION "INCREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH INCREASE IN VALUE OF ANOTHER VARIABLE OR DECREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH DECREASE IN VALUE OF ANOTHER VARIABLE IS CALLED POSITIVE CORRELATION".

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

A positive correlation.

Related questions

Correlation coefficients measure the strength and direction of a relationship between two variables. They range from -1 to 1: a value of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation. They are commonly used in statistics to quantify the relationship between variables.

No, it indicates an extremely strong positive 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.

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 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.

1.

The value of a correlation coefficient reflects the strength and direction of the relationship between two variables. A correlation coefficient ranges from -1 to 1, with 1 indicating a perfect positive relationship, 0 indicating no relationship, and -1 indicating a perfect negative relationship.

Correlation is a statistical measure that indicates the extent to which two or more variables fluctuate together. A positive correlation indicates the extent to which those variables increase or decrease in parallel; a negative correlation indicates the extent to which one variable increases as the other decreases.

I believe you are asking how to identify a positive or negative correlation between two variables, for which you have data. I'll call these variables x and y. Of course, you can always calculate the correlation coefficient, but you can see the correlation from a graph. An x-y graph that shows a positive trend (slope positive) indicates a positive correlation. An x-y graph that shows a negative trend (slope negative) indicates a negative correlation.

When variables in a correlation change simultaneously in the same direction, this indicates a positive correlation. This means that as one variable increases, the other variable also tends to increase. Positive correlations are typically represented by a correlation coefficient that is greater than zero.

a strong negative correlation* * * * *No it is not. It is a very weak positive correlation.

In science, the symbol "r" typically refers to the correlation coefficient, which measures the strength and direction of a relationship between two variables. It ranges from -1 to 1, where 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation.