"""Create an educational video to explain the CFA Level 1 knowledge: one-tailed and two-tailed test 🎓 Content Requirements: Start with a clear, beginner-friendly definition of the concept Explain the core components and logic step by step Include simple numerical examples or visual analogies Add a short summary or key takeaways at the end Ensure the structure follows a logical teaching flow from concept to application 🎨 Visual and Layout Requirements: Full-screen visuals with centered, readable content Use smooth animations to transition between steps or sections Highlight important terms, formulas, and keywords with bright accent colors (e.g., yellow, red, blue) Avoid text crowding or overlap; leave clear visual spacing Use animated icons, graphs, or diagrams where appropriate (e.g., timelines, flowcharts, charts) Minimize blank space; keep each screen visually rich and balanced 🗣️ Tone and Style: Friendly, clear, and professional Focus on making the topic accessible for first-time learners Avoid excessive jargon; use plain language wherever possible Maintain alignment with CFA curriculum terminology and scope"""

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Hey future charterholders! Welcome to our CFA Level 1 series. Today, we're diving into a key concept in Quantitative Methods: understanding the difference between one-tailed and two-tailed hypothesis tests. Before we get to tails, let's quickly remember hypothesis testing. It's how we use sample data to test claims about a population. We set up a Null Hypothesis and an Alternative Hypothesis, then use data to see if there's enough evidence to reject the null. First up, the Two-Tailed Test. You use this when your research question asks if a population parameter, like the mean, is different from a specific value. You don't care if it's higher or lower, just if it's not equal. The hypotheses look like this: H-zero states the parameter equals the value, and H-a states it does not equal the value. With a two-tailed test, your rejection region is split between both tails of the distribution. If your significance level is 5%, you'd have 2.5% in the upper tail and 2.5% in the lower tail. Now, the One-Tailed Test. You use this when your research question is directional – you're only interested if the parameter is greater than OR less than a specific value. For a right-tailed test, H-a says the parameter is greater than the value. The entire rejection region is in the upper tail. Example: Is Fund Y's average return greater than 10%? For a left-tailed test, H-a says the parameter is less than the value. The entire rejection region is in the lower tail. Example: Is Fund Z's average return less than 10%? So, how do you choose? It all depends on your research question and what you're trying to prove with your Alternative Hypothesis. The key is to look at what your Alternative Hypothesis claims. If you're testing for any difference, use two tails. If you're testing for a specific direction - greater or less - use one tail. The research question determines your Alternative Hypothesis, which then determines whether you need a one-tailed or two-tailed test. To sum up: Two-tailed tests check for any difference, splitting the rejection region between both tails. One-tailed tests check for a specific direction - greater or less - putting the whole rejection region in one tail. The key is to define your Alternative Hypothesis correctly based on what you want to test. Mastering this distinction is crucial for CFA Level 1. Keep practicing hypothesis testing problems! Remember, the research question determines your Alternative Hypothesis, which then determines your test type.