|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/clinical-research-biostatistics-wolfram
课程评论：没有评论
课程名称：临床研究：使用Wolfram语言的生物统计学 课程概述：本课程旨在帮助学员掌握统计测试技能，以便将其应用于论文、研究报告和演示中。能够总结数据、创建图表以及进行文献中常见的统计测试是一项重要能力，能够促进您的职业发展，并助力科学研究的进步。随着Wolfram语言的学习，您将能够轻松上手并迅速成为专家。 课程结构： - 第一周：介绍课程目标和Wolfram语言的应用动机，帮助学员掌握统计分析的新技能。将讲解如何获取所需软件，包括免费的网络版本和桌面版本（如有机构授权可免费使用）。 - 第二周：开始实际编码，演示一个完整项目的示例，随后学习基本的算术运算，为数据分析做准备。 - 第三周：数据分析的启动，包括数据的总结和可视化。使用描述性统计和各种图表（如箱线图、散点图等）来理解数据。同时引入可选的机器学习荣誉课程。 - 第四周：覆盖常见的统计测试（如t检验、方差分析和卡方检验），并总结课程所学，准备最终考试。学员有机会创建自己的计算散文，参加计算项目，进一步深入学习深度学习。 本课程适合所有对临床研究和数据分析感兴趣的人，无需编程基础。
Name:Week 1
Description:This first week establishes the aims of the course and motivation for using the Wolfram Language. We aim to support you in gaining a remarkable new set of skills for doing statistical analysis that you can continue to use long after you complete the course. We will also describe the process of procuring the software that you will use in the course. The first is the absolutely free version, which is software as a service, meaning it runs in any web browser. The second is the desktop version. If you work or study at an institution with a site licence, you will be able to get the software for free. There is also the option to purchase your own licence.
Name:Week 2
Description:In week 2, we start with some actual coding, now that you know about the Wolfram Language and its different coding environments. We start off with a demonstration of a completed project. It is just a little teaser, showcasing what you will be able to do at the end. Next, we are going to learn to code by doing simple arithmetic. That is simple addition, subtraction, multiplication, and so on. Once you have realized just how simple these tasks are, you will be introduced to the way in which data is stored in a computer language. These are the stepping stone required to bringing in your own data, ready for the analyses in the following weeks.
Name:Week 3
Description:In week 3, its time to start analyzing data, now that you can write some code and import your data. The two most important steps to understand the message hidden in data, are to summarize and visualize it. Descriptive statistics turn rows and columns of data into something that we as humans can understand. By summarizing values and replacing them with single values, we start to get an idea of what our analyses might show. Visualizing the data is an even better way of getting to grips with data. Box-and-whisker plots, scatter plots, bar charts, and the like are wonderful ways to augment your understanding of the data. The Wolfram Language makes summary statistics easy but it really shines when creating plots. There are almost no limits to customizing plots. No matter what your project requirements, you will learn to create plots that work for you. Starting this week is an optional Honors lessons that introduce machine learning using the Wolfram Language.
Name:Week 4
Description:This final week covers all the common statistical tests - going from Student's t-test to analysis of variance to chi-squared tests. We conclude the course with a run-through of the demonstration research project that you saw at the beginning of week two. This brings together all the skills that you have acquired during the course and prepares you for the final exam. You will also have the opportunity to create your own computational essay, if you are not content with just working through the demonstration project. For those following the optional Honors lessons there is an introduction to deep learning using the Wolfram Language.
This course has a singular and clear aim, to empower you to do statistical tests, ready for incorporation into your dissertations, research papers, and presentations. The ability to summarize data, create plots and charts, and to do the tests that you commonly see in the literature is a powerful skill indeed. Not only will it further your career, but it will put you in the position to contribute to the advancement of humanity through scientific research. We live in a wonderful age with great tools at our disposal, ready to achieve this goal. None are quite as easy to learn, yet as powerful to use, as the Wolfram Language. Knowledge is literally built into the language. With its well-structured and consistent approach to creating code, you will become an expert in no time. This course follows the modern trend of learning statistical analysis through the use of a computer language. It requires no prior knowledge of coding. An exciting journey awaits. If you wanting even more, there are optional Honors lessons on machine learning that cover the support in the Wolfram Language for deep learning.
