This content originally appeared on DEV Community and was authored by Aditi Sharma
P-Value & Critical Region in Probability 
Today I explored two important concepts in hypothesis testing:
P-Value
β’ Probability of getting results at least as extreme as observed, assuming the null hypothesis is true.
β’ Low p-value (< 0.05) β strong evidence against null hypothesis.
Critical Region
β’ The range of values where we reject the null hypothesis.
β’ Defined by significance level (Ξ±), often 5%.
Why it matters?
P-value tells us how surprising our result is.
Critical region decides whether to accept or reject a hypothesis.
Fun Fact: The 0.05 threshold for p-values was first popularized by Ronald Fisher in the 1920s β and it still rules data science & research today! 
Python #Statistics #Probability #100DaysOfCode #DataAnalytics
This content originally appeared on DEV Community and was authored by Aditi Sharma