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Get our FREE CFA Level 1 summaries: https://www.finquiz.com/cfa/level-1/summary 📉 Quant Methods Got You Spiraling? FinQuiz = Your CFA Lifeline Quant isn’t just plug-and-chug. It’s logic, timing, and not getting trapped on exam day. Whether you're battling z-scores or trying to remember if it's n or n–1, we’ve got your back. 📎 Battle-Ready Summaries – No fluff, no chaos. Just the core Quant ideas, explained clearly 👉 https://www.finquiz.com/cfa/level-1/summary/ 🧷 Stanley Notes – Clean breakdowns of complex concepts (yes, even heteroskedasticity) 👉 https://www.finquiz.com/cfa/level-1/notes/ 📌 Formula Sheet – All the essentials on one page. Screenshot it. Tattoo it. Just don’t forget it. 👉 https://www.finquiz.com/cfa/level-1/formula-sheet/ 🎮 Question Bank – Practice like you mean it. Real CFA-style traps, logic puzzles, and curveballs 👉 https://www.finquiz.com/cfa/level-1/question-bank/ ⏱ Mock Exams – Time pressure. Real feel. Actual anxiety simulator (but also confidence booster) 👉 https://www.finquiz.com/cfa/level-1/mock-exam/ 🧃 Explore All CFA Level 1 Resources 👉 https://www.finquiz.com/cfa/level-1/ 💸 Want the full upgrade? Go Premium = Everything unlocked + guidance to crush Level 1 👉 https://www.finquiz.com/cfa-level-1-study-packages/ 0:00 Introduction: Statistical Inference & Hypothesis Testing Overview of statistical inference (making judgments from samples) Why hypothesis testing matters in finance (objective decision-making) 0:53 Key Concepts: Null vs. Alternative Hypothesis Null hypothesis (default assumption with equality) Alternative hypothesis (the “challenger”) How they shape hypothesis testing in finance 1:29 Steps in Hypothesis Testing State hypotheses (null & alternative) Choose test statistic (Z, t, etc.) Set significance level (alpha) Decision rule & critical values Collect data & calculate test statistic Compare to critical region Make economic/financial decision 3:04 One-Tailed vs. Two-Tailed Tests Detecting differences in a specific direction (one-tail) Checking for any significant difference (two-tail) Examples in investment return hypotheses 5:30 Type I & Type II Errors Type I (false positive, alpha) Type II (false negative, beta) Trade-off between lowering alpha and raising beta 7:06 Testing Means: Single Mean & Differences Single mean hypothesis test (Z or t) Two independent means (t-test for independent samples) Paired samples (before/after testing) 10:56 Testing Variances: Chi-Square & F-Test Single variance (chi-square distribution) Comparing two variances (F distribution) Decision rules for rejecting the null 14:11 Parametric vs. Non-Parametric Tests Parametric: assumes known distribution (normal), focuses on parameters (mean, variance) Non-parametric: minimal distributional assumptions (e.g., Mann-Whitney, Wilcoxon) When to use each method 18:48 Conclusion & CFA Exam Prep Tips Recap of hypothesis testing importance Balancing type I and type II errors Practicing parametric & non-parametric approaches Encouragement for CFA success