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Why there is no degrees of freedom in Z test?
so
Why is it impossible to compute a T statistic for a sample that has only one score?
A T test is used to find the probability of a scenario given a specific average and the number of degrees of freedom. You are free to use as few degrees of freedom as you wish, but you must have at least 1 degree of freedom. The formula to find the degrees of freedom is "n-1" or the population sample size minus 1. The minus 1 is because of the fact that the first n is not a degree of freedom because it is not an independent data source from the original, as it is the original. Degrees of freedom are another way of saying, "Additional data sources after the first". A T test requires there be at least 1 degree of freedom, so there is no variability to test for.
How do you use the F Test to find the sample size for two sets of data?
The data sets determine the degrees of freedom for the F-test, nit the other way around!
What is the table value of 5 percent significant level in f test?
It depends on the degrees of freedom for the f-test.
In a two-way contingency table with four rows and four columns the appropriate degrees of freedom for the chi-square test statistic is?
The degrees of freedom for any contingency table can be calculated simply by the formula (r-1)x(c-1) where r= the number of rows and c= the number of columns. Thus for a contingency table with four rows and four columns the degrees of freedom are 3x3 = 9.
