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所在平台: Udemy |
课程主页: https://www.udemy.com/course/correlations-associations-and-hypothesis-testing-with-r/
课程评论：没有评论
《相关性、关联性和假设检验（使用R）》课程总结 本课程旨在帮助学习者深入理解统计分析与机器学习中的核心概念——变量（特征）之间关联性的评估与量化，以及假设检验。课程内容适合初级分析师和经验丰富的数据科学家，旨在为初学者打下坚实基础，并帮助有经验者巩固和提升对关联性评估的理解。 课程结构分为三个主要部分： 1. **数值变量间的关联性评估：** 探讨和量化数值型变量之间的关系强度。 2. **分类变量间的关联性评估：** 关注分类型变量之间的关联性分析。 3. **数值与分类变量间的关联性评估：** 涵盖数值型变量与分类型变量之间关联性的度量。 在每个部分中，课程都将深入介绍相关的统计指标，并在此基础上构建统计假设检验方法，以衡量这些关联的强度。课程包含大量的实践环节，通过使用 **R语言** 和真实数据集，学习者将亲手实践所学方法，执行各种假设检验，并**学会如何全面解读结果**。 此外，每部分结束后都设有**测验**，旨在帮助学习者巩固所学概念。 完成本课程后，学习者将能够清晰、连贯地理解**协方差、相关性、t检验、卡方检验、方差分析（ANOVA）、F检验**等关键统计工具，并掌握它们的使用场景以及如何确保满足其**基本假设**。
Exploring and assessing the strength of associations between variables/features plays a fundamental role in statistical analysis and machine learning. I decided to create this course after leading many data science projects and coming across many data scientists struggling with the fundamentals of association between variables/features and hypothesis testing. This course will be beneficial to junior analysts as well as to more experienced data scientists. In particular,If you are an aspiring/junior data analyst/scientist, this course will contribute towards building the right foundation at an early stage of your career.If you are an experienced data scientist, this course will help you to re-visit and eventually improve your understanding of the assessment of associations between variables/features.The course is divided into three main sections.The first section looks at the assessment and quantification of associations between numerical variables.The second section focusses on the assessment of associations between categorical variables.The third section covers the assessment of associations between numerical and categorical variables.Each section discusses a number of statistical metrics in relation to associations between variables and then build statistical hypothesis tests to measure the strengths of these associations. There are practical sessions throughout the course, where you will see how to implement the methods discussed in the course (using R) and to perform various hypothesis testing using real world datasets. Your will also learn and master how to interpret results in a broader context.In addition, quiz is added at the end of each section. The objective of these quizzes is to help you to consolidate the main concepts covered in the course.By the end of the course, you will have a clear and coherent understanding of covariances, correlations, t-test, Chi-squared test, ANOVA, F-test, and much more. In particular, you will know when to use these tests and how to ensure that the underlying assumptions are satisfied.
