The term probable error is seen only in older statistics literature where it used to denote the product of the standard error and a constant factor 0.6745. Thus,
P.E = 0.6745(S.E)
Here P.E and S.E stand for the probable error and the standard error, respectively. By using the above formula the probable error of any statistic may be determined if we substitute the standard error of that statistic. Hence, for example, the probable error of the correlation coefficient would be
Definition: The Probable Error of Correlation Coefficient helps in determining the accuracy and reliability of the value of the coefficient that in so far depends on the random sampling.
In other words, the probable error (P.E.) is the value which is added or subtracted from the coefficient of correlation (r) to get the upper limit and the lower limit respectively, within which the value of the correlation expectedly lies.
The probable error of correlation coefficient can be obtained by applying the following formula:
r = coefficient of correlation
N = number of observations
where rho denotes the correlation in a population
The probable Error can be used only when the following three conditions are fulfilled:
Thus, the probable error is calculated to check the reliability of the value of coefficient calculated from the random sampling.
|1. What is correlation and regression in business mathematics and statistics?
|2. How is correlation calculated?
|3. What is the difference between correlation and regression?
|4. How is regression analysis used in business?
|5. What are the limitations of correlation and regression analysis?