Is an R-Value of 0.93 Considered Strong in Social Sciences?

In summary, a correlation coefficient of r=0.93 is considered high. It means that most of the variation in the y values can be explained by the regression equation.
  • #1
qspeechc
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Hello everyone.

I stumbled across an article in the social sciences that had a correlation coefficient of r=0.93.

Being from a maths background and knowing nothing about things like social sciences, psychology, etc., is this r-value in these types of fields considered fairly strong, strong, weak...? Or what?

Cheers
 
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  • #2
If you have two variables, x, and y, with a correlation of r, that means that r^2 of the variation in y can be explained by the variation in x. For example, height and weight have an r around 0.8 or so.
 
  • #3
Haha, I know what the correlation coefficient means, I'm asking in the field of social sciences, psychology etc., is r=0.93 considered high? Mediocre? What?
 
  • #4
It's high. It means that most of the variation of the y values can be explained by the regression equation. The fraction of variation that is explained is r2 = 0.86.

You should be judicious when drawing conclusions about relationships with a high r value. Two variables can have very similar trends even if there is no connection between them. The population of the Earth and the age of the Solar system both increase, but that does not mean that they are related.

I think it is reasonable to say that variation of y which looks random, but can be largely explained by variation of x is more likely to indicate a connection between the two variables.
 
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  • #5
That's roughly the same correlation as the number of honey bee colonies in the US and the marriage rate in Vermont.

honey-producing-bee-colonies-us_marriage-rate-in-vermont.png
 
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  • #6
Ah, so the r2 value is more important?
 
  • #7
Vanadium 50 said:
That's roughly the same correlation as the number of honey bee colonies in the US and the marriage rate in Vermont.

View attachment 211777
This is a good example of two variables with general downward trends giving a high r2 regression value. But it also shows a periodic component that looks synchronized, driving the r2 value even higher. This is where the scientist must be judicious in his conclusions. If he searched the world for something to match to the bee hive numbers, then he is bound to find something. If he had some a priori reason to relate bee hive numbers to the marriage rate, then this is some supporting information. (I can't imagine any a priori reason.)

PS. I wonder if the data shown is real or is fictitious to make a point?
 
  • #8
FactChecker said:
I wonder if the data shown is real or is fictitious to make a point?

As far as I know, it is real. It is from the "Spurious Correlations" page at www.tylervigen.com. It has other great ones - "Divorce rate in Maine" and "Per capita consumption of margarine" at r = .9926.
 
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  • #9
If it's in psychology, and there haven't been replication attempts yet, I'd ignore it. There's something of a replication crisis still brewing out there.
 
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What is R value in social sciences?

R value, also known as the Pearson correlation coefficient, is a statistical measure of the strength and direction of the linear relationship between two variables in a dataset. It ranges from -1 to 1, where -1 indicates a perfect negative relationship, 0 indicates no relationship, and 1 indicates a perfect positive relationship.

Why is R value important in social sciences?

R value is important in social sciences because it allows researchers to determine the strength and direction of the relationship between two variables. This information is crucial in understanding and making predictions about social phenomena.

How is R value calculated?

R value is calculated by dividing the covariance of the two variables by the product of their standard deviations. It can also be calculated using statistical software or calculators.

What is a good R value?

There is no definitive answer to what constitutes a good R value as it depends on the context and variables being studied. In general, an R value closer to 1 or -1 indicates a strong relationship, while a value closer to 0 indicates a weak relationship.

Can R value be used to establish causation?

No, R value only shows the strength and direction of the relationship between two variables. It cannot determine causation, as there may be other variables at play that are not accounted for in the analysis.

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