|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/statistics-fundamentals-bundled/
课程评论：没有评论
课程名称：统计学基础 课程概述：欢迎参加《统计学基础》课程！本课程适合初学者以及希望复习基础知识的学习者。统计学作为一门科学，关注数据的收集、数学分析、描述数据及从数据中进行推断。通过统计方法，我们可以从数据中获得洞察，帮助我们解答各种问题并做出决策。统计分析现已广泛应用于各个科学和实际领域，包括自然科学和社会科学。在商业实践中，统计分析被应用于人力资源分析和市场分析等业务分析中；在医学实践和政府政策制定中，它也是一种重要工具。此外，棒球队利用统计数据来制定战略，这就是著名的SABRmetrics。如果我们不使用适当的方法，统计分析可能会导致无意义或误导性的结果。为了从数据中获得有意义的洞察，我们需要从实践和理论两个方面学习统计学。本课程的目的是为您提供理论知识和Python编码技能，理论知识使我们能够在各种情境中实施适当的分析，同时也是更高阶学习的有用基础。 本课程是一个全面的统计学基础学习项目，共有9个部分，涵盖理论内容和基本的Python编码。即使您没有Python编程经验，我相信您也能轻松跟上。但本课程并不是专门的Python课程，因此不涵盖如何安装Python和构建环境的内容。虽然本课程设计为初学者使用，但通过学习，您将达到统计学的中级水平，具体内容涵盖本科水平的统计学。注册后，您可以在第一节的页面上下载讲义、Python代码文件和玩具数据集。 课程大纲： 1. 课程介绍 2. 描述性统计 3. 概率 4. 概率分布 5. 抽样 6. 估计 7. 假设检验 8. 相关性与回归 9. 方差分析（ANOVA） 期待在课程中见到您！
Welcome to Statistics Fundamentals! This course is for beginners who are interested in statistical analysis. And anyone who is not a beginner but wants to go over from the basics is also welcome!As a science field, statistics is a discipline that concerns collecting data, and mathematical analysis of the collected data, describing data and making inference from the data. Using statistical methods, we can obtain insights from data, and use the insights for answering various questions and decision making. Statistical Analysis is now applied in various scientific and practical fields. It is essential in both natural science and social science. In business practice, statistical analysis is applied as business analytics such as human resource analytics and marketing analytics. And now, it is an essential tool in medical practice and government policymaking. Besides, baseball teams utilize it for strategy formation. It is well known a SABRmetrics. However, if we do not use appropriate methods, statistical analysis will result in meaningless or misleading findings. To obtain meaningful insights from data, we need to learn statistics both in practical and theoretical viewpoints. This course intends to provide you with theoretical knowledge as well as Python coding. Theoretical knowledge enables us to implement appropriate analysis in various situations. And it can be a useful foundation for more advanced learning.This course is a comprehensive program for learning the basics of statistics. It consists of the 9 sections. They cover theory and basic Python coding. Even if you do not have Python coding experience, I believe they are easy to follow for you. But this program is not a Python course, so how to install Python and construct environment is not covered in this course.This course is designed for beginners, but by learning with this course, you will reach an intermediate level of expertise in statistics. Specifically, this course covers undergraduate level statistics. After enrollment, you can download the lecture presentations, Python code files, and toy datasets in the first lecture page.I'm looking forward to seeing you in this course!*In some videos, the lecturer says ".will be covered in later courses", but it should be "later sections." Table of Contents1. Introduction2. Descriptive Statistics: 3. Probability4. Probability Distribution 5. Sampling6. Estimation7. Hypothesis Testing8. Correlation & Regression9. ANOVA
