What do t, p, r mean in Studies?

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In studies, "t" refers to a test statistic from the t-distribution, which is used in hypothesis testing, while "p" denotes the p-value, indicating the probability that results occurred by chance under the null hypothesis. The "r" represents the sample correlation coefficient, measuring the strength and direction of a linear relationship between two variables, ranging from -1 to 1. Beta symbols indicate regression coefficients in statistical models. The discussion highlights the importance of understanding these statistical terms for interpreting research findings, particularly in psychological studies. Overall, these notations are essential for analyzing data and drawing conclusions in scientific research.
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In studies, they always refer to certain variable values or something. Like: one-sample t (64) = 7.02, p < .0001. This overestimation occurred even though self-ratings of ability were significantly correlated with our measure of actual ability, r (63) = .39, p < .001 or This was true for the first set of self-appraisals, &Beta s(67) = - .40 to - .49, p s < .001, as well as the second, &Beta s(67) = - .41 to - .50, p s < .001

what are t, p, r etc. ? :confused:

I know I should know this but it's been a looooooong time.


Poop. Those "&Beta"s are meant to be Beta symbols.
 
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Can you provide a link to the entire source material? It is possible that this is some kind of notation common in the field from which this quote came from.

- Warren
 
This sounds like an abstract from a psychological studies. I am not sure about the symbols. But in general in statistics, "r" refers to the "sample correlation coefficient" between two variables. "r" lies in the range from -1 to 1. A positive (negative) value indicates a positive (negative) *linear* correlation between the two variables. Since in studies we can only take a finite number of samples, we can only hope to estimate r using the data that are available to us. In this process of estimation there is likely to be "errors".

As to "p", it is called the "p value" and 1-p is called the "confidence level". It is tied with something called "hypothesis testing" in statistics. I do not see any hypothesis in the piece of writing so I cannot explain it.

As to the one sample t and beta, I think they are some "test statistics" for some hypothesises. But without knowing the hypothesises I cannot say any further.
 
"t(n)" most likely refers to t-distribution of n degrees of freedom and "p" is the probability that the given "t" results could have occurred purely by chance given the "null hypothoses". Note the a "t" distribution is a common probability density function that is quite similar to the Normal distribution. The quoted example is a little unusual as "t" distributions with degrees of freedom greater than 30 are rarely used as they are extremely well approximated with the normal distribution.

"r" is a corelation coefficient, and "Beta" is yet another distribution function.
 
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Thanks guys. That was indeed from a psychological study (http://www.apa.org/journals/psp/psp7761121.html - a most interesting read!), but I've seen similar notation in numerous other places. thanks again.
 
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