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所在平台: Udemy |
课程主页: https://www.udemy.com/course/master-hypothesis-testing-statistics-help/
课程评论：没有评论
课程名称：统计学：中心极限定理与假设检验 课程概述：本课程是建立优秀推断统计学理解的关键，已有来自100多个国家的学生参与。许多学生表示：“解释得非常清楚，每个概念都明了易懂，绝对值得购买。”~ K Roshnishree。“解释非常直观，课程中包括的练习题有助于巩固概念。”~ Swati Sahu。“对基础主题的详细讲解非常惊人。”~ Rehana Shake。“这位讲师在统计概念的解释方面做得很好。”~ Frank Herrera。“非常清晰的例子，谢谢您！”~ Gitartha Pathak。 课程描述：本课程旨在帮助在统计学上遇到困难或对统计学完全陌生的学生。 课程结构： 第1和第2部分：这两部分涵盖了理解假设检验基础所必需的重要概念——正态分布、标准正态分布、抽样、抽样分布和中心极限定理。（在开始假设检验之前，请确保您对这些概念有清晰的理解） 第3部分：这一部分介绍假设检验的基础知识，采用三种方法——临界值方法、Z分数方法和p值方法。 教学方式：我的教学方式是实践导向的：概念、例子和解决问题，全面覆盖讲座中的所有概念。 注意：仅覆盖单一总体均值的假设检验。
This course is the key to build an excellent understanding of Inferential Statistics. It has students (from over 100 countries) and here is what some of them have to say: "Well explained sir, every concept is clear as water and the way you explain is very easy to understand the concept. Worth buying this course" ~ K Roshnishree"The explanations are quite intuitive and the best part is that the course includes practice problems which helps in building the concepts" ~ Swati Sahu"The detail level coverage of the basic topics is amazing" ~ Rehana Shake"This instructor is doing a fine job explaining the statistics concepts" ~ Frank Herrera"Very clear examples, thank you sir!" ~ Gitartha PathakCourse Description: This course is designed for students who are struggling with Statistics or who are complete beginners in statistics.How is this course structured? Section 1 and 2: These 2 sections cover the concepts that are crucial to understand the basics of hypothesis testing - Normal Distribution, Standard Normal Distribution, Sampling, Sampling Distribution and Central Limit Theorem. (Before you start hypothesis testing, make sure you are absolutely clear with these concepts)Section 3: This section caters to the basics of hypothesis testing with three methods - Critical Value Method, Z-Score Method and p-value method.My approach is hands on: Concepts, examples and solved problems addressing all the concepts covered in the lectures.Note: Only Hypothesis Testing in Case of Single Population Mean is covered
