Right tailed or upper tailed test
A right-tailed test or upper test is the inequality that is pointing to the right.
Example:
Python
# importing packages import scipy.stats # finding p-value p_value = scipy.stats.norm.sf( abs ( 1.67 )) print ( 'p value is : ' + str (p_value)) |
Output:
p value is : 0.04745968180294733
In case we choose the level of significance or alpha value as 0.05. the p-value is less than the alpha value (0.05) so the alternative hypothesis is accepted and null hypothesis is rejected.
How to Find a P-Value from a Z-Score in Python?
The p-value in statistics is the likelihood of getting outcomes at least as significant as the observed results of a statistical hypothesis test, given the null hypothesis is true. The p-value, rather than rejection points, is used to determine the least level of significance at which the null hypothesis is rejected. A lower p-value indicates that the alternative hypothesis has more evidence supporting it, if a p-value is high alternative hypothesis is rejected and the null hypothesis is rejected. In this article let’s demonstrate how to find a p-value from a z-score in python.
We use scipy.stats.norm.sf() function for calculating p-value from z-score.
Syntax:
scipy.stats.norm.sf(Z_value)
if z_value is less than zero then we use :
scipy.stats.norm.sf(abs(Z_value))
Contact Us