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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/statistical-thinking-applied-statistics
课程评论：没有评论
课程名称：统计思维与工业问题解决，由JMP提供 概述： 《统计思维与工业问题解决》是一门由JMP（SAS的一个部门）提供的应用统计学课程，旨在帮助科学家和工程师理解统计思维的重要性，并利用数据和基本统计方法解决多种现实世界中的问题。完成此课程后，学生将能够： - 解释统计思维在解决问题中的重要性 - 描述数据的重要性以及为分析整理和准备数据的步骤 - 比较用于总结、探索和分析数据的核心方法，并描述何时应用这些方法 - 认识到统计设计实验在理解因果关系中的重要性 课程大纲： 1. 课程概述：了解课程内容及如何访问JMP软件。 2. 模块1：统计思维与问题解决：学习理解、控制和减少过程变异的统计思维，包括过程图和问题解决工具。 3. 模块2A：探索性数据分析，第一部分：了解如何使用基本图形和统计汇总描述数据，以及更高级的可视化方法来探索数据。 4. 模块2B：探索性数据分析，第二部分：学习如何使用交互式可视化有效传达数据故事，以及如何保存和共享结果，准备数据进行分析。 5. 模块3：质量方法：学习量化、控制和减少产品、服务或过程中的变异的工具，包括控制图、过程能力和测量系统分析。 6. 模块4：基于数据的决策：学习用于从数据中推断的工具，包括统计区间和假设检验，并了解样本大小与能力之间的关系。 7. 模块5：相关性与回归：使用散点图和相关性研究变量之间的线性关系，学习拟合、评估和解释线性与逻辑回归模型。 8. 模块6：实验设计（DOE）：介绍统计设计实验的语言，学习如何设计、实施和分析JMP中的实验。 9. 模块7：预测建模与文本挖掘：识别可能的关系、构建预测模型以及从非结构化文本中提取价值。 10. 复习问题与案例研究：测试您对所学内容的理解的机会。 这个课程通过全面的内容和实用的技能，帮助学员在工业领域中应用统计思维解决实际问题。
Name:Course Overview
Description:In this module you learn about the course and about accessing JMP software in this course.
Name:Module 1: Statistical Thinking and Problem Solving
Description:Statistical thinking is about understanding, controlling and reducing process variation. Learn about process maps, problem-solving tools for defining and scoping your project, and understanding the data you need to solve your problem.
Name:Module 2A: Exploratory Data Analysis, Part 1
Description:Learn the basics of how to describe data with basic graphics and statistical summaries, and how to explore your data using more advanced visualizations. You’ll also learn some core concepts in probability, which form the foundation of many methods you learn throughout this course.
Name:Module 2B: Exploratory Data Analysis, Part 2
Description:Learn how to use interactive visualizations to effectively communicate the story in your data. You'll also learn how to save and share your results, and how to prepare your data for analysis.
Name:Module 3: Quality Methods
Description:Learn about tools for quantifying, controlling and reducing variation in your product, service or process. Topics include control charts, process capability and measurement systems analysis.
Name:Module 4: Decision Making with Data
Description:Learn about tools used for drawing inferences from data. In this module you learn about statistical intervals and hypothesis tests. You also learn how to calculate sample size and see the relationship between sample size and power.
Name:Module 5: Correlation and Regression
Description:Learn how to use scatterplots and correlation to study the linear association between pairs of variables. Then, learn how to fit, evaluate and interpret linear and logistic regression models.
Name:Module 6: Design of Experiments (DOE)
Description:In this introduction to statistically designed experiments (DOE), you learn the language of DOE, and see how to design, conduct and analyze an experiment in JMP.
Name:Module 7: Predictive Modeling and Text Mining
Description:Learn how to identify possible relationships, build predictive models and derive value from free-form text.
Name:Review Questions and Case Studies
Description:In this module you have an opportunity to test your understanding of what you have learned.
Statistical Thinking for Industrial Problem Solving is an applied statistics course for scientists and engineers offered by JMP, a division of SAS. By completing this course, students will understand the importance of statistical thinking, and will be able to use data and basic statistical methods to solve many real-world problems. Students completing this course will be able to: • Explain the importance of statistical thinking in solving problems • Describe the importance of data, and the steps needed to compile and prepare data for analysis • Compare core methods for summarizing, exploring and analyzing data, and describe when to apply these methods • Recognize the importance of statistically designed experiments in understanding cause and effect
