P-Value & Critical Region in Probability 📊
Today I explored two important concepts in hypothesis testing:
🔹 P-Value
• Probability of getting results at least as extreme as observed, assuming the null hypothesis is true.
• Low p-value (< 0.05) → strong evidence against null hypothesis.
🔹 Critical Region
• The range of values where we reject the null hypothesis.
• Defined by significance level (α), 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 — and it still rules data science & research today! 📖
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