Let us learn about p value formula
The p-value is referred as the area under the null distribution curve which is in bigger disagreement with the null hypothesis than the observed test statistics.
Best example, the hypothesis test for the mean is:
Imagine you have a large enough sample such that the central limit theorem holds & the mean is normally distributed then to test the null hypothesis H0: μ = Δ
find the test statistic “z” = (x Bar - Δ) / (sx / square root (n)) where “x” bar is the sample average
sx is the sample standard deviation
”n” is the sample size
The p value formula of the test is the area under the normal curve which is in agreement with the alternate hypothesis.
H1: μ > Δ; p-value is the area to the right of z
H1: μ < Δ; p-value is the area to the left of z
H1: μ ≠ Δ; p-value is the area in the tails is always greater than |z|
for a small test for the mean every thing is the same save the test statistic is a t statistic with n - 1 degrees of freedom. In such case the underlying distribution should be normal for this test to be valid.
In our next blog we shall learn about sexual reproduction in humans I hope the above explanation was useful.Keep reading and leave your comments.
The p-value is referred as the area under the null distribution curve which is in bigger disagreement with the null hypothesis than the observed test statistics.
Best example, the hypothesis test for the mean is:
Imagine you have a large enough sample such that the central limit theorem holds & the mean is normally distributed then to test the null hypothesis H0: μ = Δ
find the test statistic “z” = (x Bar - Δ) / (sx / square root (n)) where “x” bar is the sample average
sx is the sample standard deviation
”n” is the sample size
The p value formula of the test is the area under the normal curve which is in agreement with the alternate hypothesis.
H1: μ > Δ; p-value is the area to the right of z
H1: μ < Δ; p-value is the area to the left of z
H1: μ ≠ Δ; p-value is the area in the tails is always greater than |z|
for a small test for the mean every thing is the same save the test statistic is a t statistic with n - 1 degrees of freedom. In such case the underlying distribution should be normal for this test to be valid.
In our next blog we shall learn about sexual reproduction in humans I hope the above explanation was useful.Keep reading and leave your comments.
