SA-EP7-Kruskal-Wallis Test in Statistics [ ENGLISH ]

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SA-EP7-Kruskal-Wallis Test in Statistics [ ENGLISH ]

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🎙️ Episode Title: Kruskal–Wallis Test – The Non-Parametric ANOVA 🔍 Episode Description: Welcome to another enlightening episode of “Pal Talk – Statistics”, where we bring the world of numbers to life! In today’s episode, we explore a non-parametric powerhouse in hypothesis testing — the Kruskal–Wallis H Test. If you're working with three or more independent groups and your data isn’t normally distributed, then this test could be your go-to tool. Think of it as the non-parametric cousin of ANOVA — but without the strict assumptions. In this episode, we uncover: ✅ What is the Kruskal–Wallis Test? The Kruskal–Wallis Test is used to compare the medians of three or more independent groups when assumptions for parametric ANOVA are not met. It uses ranked data instead of raw values, making it robust and reliable in real-world scenarios. ✅ Why Use Kruskal–Wallis Instead of ANOVA? We explain how this test shines when: The sample sizes are small Data is skewed or contains outliers You're dealing with ordinal or non-normal data This makes it ideal for surveys, psychological scales, biological measures, and more. ✅ Step-by-Step Explanation Setting up null and alternative hypotheses Ranking the combined dataset Calculating the test statistic (H) Interpreting the result using the chi-square distribution Our hosts walk through the entire process with a relatable example — comparing customer satisfaction ratings from three different service centers. ✅ Post Hoc Tests After Kruskal–Wallis A significant result tells you there’s a difference — but not where it is. Learn about Dunn’s test and pairwise comparisons for diving deeper after significance. ✅ Assumptions of the Test Even non-parametric tests have some rules. We cover the key assumptions, such as independent samples and similar distribution shapes. ✅ Real-World Applications Comparing medication effects across different dosage groups Evaluating teaching methods across multiple classrooms Studying behavioral patterns across age groups in psychology ✅ Kruskal–Wallis vs One-Way ANOVA We make the comparison easy to remember — from assumptions to output, helping you choose the right test every time. 👥 Hosts: Speaker 1 (Male): A researcher with a passion for robust statistics. Speaker 2 (Female): A lifelong learner asking practical questions to clarify every concept. 🎧 Whether you're analyzing social science data, working with clinical trials, or conducting survey research — the Kruskal–Wallis Test is a valuable tool in your statistical toolbox. Tune in to understand how and when to use it confidently! 📌 Coming Up on “Pal Talk – Statistics”: Dunn’s Post Hoc Test Friedman Test for Related Samples Effect Size in Non-Parametric Tests Visualizing Ranked Data 💡 Like what you hear? Subscribe, share, and rate “Pal Talk – Statistics” to support your favorite destination for practical and professional statistics talk. 🎓 Pal Talk – Where Data Talks.