SPSS para Estadística No Paramétrica

¡Descubre el Poder del Análisis de Variables Cualitativas con SPSS!

🌟 Course Title: SPSS para Estadística No Paramétrica
🎓 Instructor: Saul Arellano Almanzana

Course Headline:

Domina las Variables Categóricas con el Curso Completo de Análisis No Paramétrico en SPSS

Course Description:

Introduction to the Course: Welcome to a comprehensive journey into the world of Non-Parametric Statistics using SPSS, specifically tailored for handling categorical variables. This course will empower you with the skills needed to confidently perform robust statistical analyses that don't rely on the assumptions typically required in Parametric Tests.

Key Learning Points:

• Mastery of SPSS: Learn to effectively navigate and utilize this powerful statistical tool to manage categorical data.
• Non-Parametric Analysis: Understand when and why these tests are necessary, especially when your data doesn't meet the assumptions for Parametric Tests.
• Contingency Tables and Objectives: Dive into interpreting contingency tables and selecting the appropriate statistical test based on your objectives.
• Real-World Applications: Work through practical examples using actual data from official sources, ensuring you learn by applying concepts in real scenarios.
• Xi-Squared Analysis: Explore the Xi-Square statistic and its variations to analyze cases and controls, before-and-after scenarios, and test for independence between variables.
• Advanced Topics: Discover additional tests like the Cohen's Kappa and Cochran's Q for more in-depth analysis.

Course Outline:

1. Introduction to Non-Parametric Tests: Understand why these tests are essential and learn how they can be used as a tool to explore data that doesn't meet the normality assumptions of Parametric Tests.
2. Contingency Tables and Contingency Coefficients (Cramér's V, Phi Coefficient): Learn how to interpret and use these tables for categorical data analysis.
3. Chi-Square Test for Independence: Gain proficiency in applying this test to assess the relationship between two categorical variables.
4. Mann-Whitney U Test and Kruskal-Wallis H Test: Learn how to compare medians between two or more independent samples when you cannot assume equal variances or normality.
5. Wilcoxon Signed-Rank Test and Friedman Test: Master these tests for paired and related samples, respectively.
6. Cohen's Kappa and Cochran's Q: Discover these advanced measures of inter-rater reliability and agreement among multiple raters, respectively.

Course Benefits:

• Enhance your understanding of non-parametric statistics and their applications in research.
• Gain the ability to interpret and report on the results of non-parametric tests within SPSS.
• Learn to identify the right statistical test for your data type and research question.
• Develop a critical skill set that is highly sought after in many fields including psychology, social sciences, public health, and more.

Prerequisites: While this course is designed to be accessible to learners at various levels, having foundational knowledge of Descriptive Statistics and basic SPSS proficiency will greatly enhance your learning experience and ability to apply the concepts taught in this course.

Join now and unlock the door to deeper data insights with SPSS and Non-Parametric Statistics! 🚀📊✨