Hypothesis Testing Masterclass: All 5 Steps Combined | Final Lecture

Welcome to the Final Lecture of the Hypothesis Testing series! In this session, we bring everything together and solve a complete, real-world Hypothesis Testing problem from scratch — applying all 5 steps in one go. In this session we cover: - A complete end-to-end solved example: "Has the average daily stock return increased from 1.2%?" - Step 1: Defining Null & Alternate Hypothesis — and identifying it as a Right Tail Test - Step 2: Choosing the right distribution — Normal Distribution - Step 3: Calculating Test Statistics using the Z-formula → Z = 1.60 - Step 4: Finding the Critical Value from the Z Table → Z critical = 1.645 - Step 5: Comparing Test Statistic vs Critical Value → Failed to Reject Null Hypothesis - Intuition building: Why 1.6% sample mean is NOT statistically far enough from the historical 1.2% - How the same 5-step logic applies to T, Chi-Square, and F distribution tests too 🔔 Subscribe for more Statistics and Data Science lecture series! Timestamps: 0:00 – Introduction: Final Lecture — Putting All Steps Together 0:23 – About This Session: No New Steps, Only Practice 0:57 – Reading the Question: Stock Return Hypothesis Problem 1:28 – Step 1: Define Hypothesis — Null & Alternate Hypothesis 1:53 – Alternate Hypothesis 2:05 – Null Hypothesis: Mean Return ≤ 1.2% 2:27 – Identifying Test Type: Right Tail Test (Greater Than Sign) 2:56 – Step 2: Choose Distribution — Normal or T? 3:03 – Mean Test → Normal or T Distribution 3:53 – Population SD Known + Sample Size 36 4:14 – Step 3: Calculate Test Statistics Using Z Formula 4:38 – Plugging in Values: x̄ = 1.6%, μ = 1.2%, σ = 1.5%, n = 36 4:55 – Test Statistic Result: Z = 1.60 5:06 – Step 4: Find Critical Value from Z Table 5:30 – Right Tail Test, 5% Significance → Look for 95% in Z Table 6:30 – Critical Value: Z = 1.645 6:46 – Step 5: Compare Test Statistic vs Critical Value 7:00 – Rejection Region vs Acceptance Region 7:13 – Z = 1.60 Falls in Acceptance Region 7:25 – Conclusion: Failed to Reject Null Hypothesis 8:12 – Intuition: Why 1.6% is Not Statistically Different from 1.2% 9:26 – Final Interpretation of Result 9:49 – Series Wrap-Up: Same 5 Steps Work for All Distributions 10:19 – Closing Remarks