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所在平台: Udemy |
课程主页: https://www.udemy.com/course/spss-data-analysis-for-beginning-researchers/
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课程名称：SPSS数据分析入门研究者 课程概述： 感谢您查看《SPSS数据分析入门研究者》课程。正如其名，该课程面向那些正在进行首次研究项目（即初学者/新手）的人群，包括但不限于：正在撰写研究论文或学位论文的学生、拥有非技术背景的初步研究者以及对数据分析感兴趣的任何人。 数据分析为何困难？ 许多人认为数据分析困难，这有其合理性。数据分析是一门多学科领域，要求整合不同领域的知识才能正确进行。进行数据分析时，您需要： 1. 数据分析软件（如SPSS、Excel、R等）的知识 2. 统计学概念的理解 3. 研究方法的掌握 4. 处理数据的经验与技能 然而，初学者往往在这些领域的知识、经验和技能上都比较匮乏。可能的情况包括：您知道怎么使用数据分析软件，但不知道应使用哪种分析方法；您了解一些统计知识，但不知如何在计算机上计算；您对统计、软件和研究有所了解，但不知道如何进行分析来满足研究需求；您可能了解统计、软件和研究，但缺乏实际处理数据的经验，面临诸如缺失数据和无效数据等实际问题。 虽然有很多关于不同学科的教科书，但很少有能涵盖这些知识和技能的教材。信息过剩的现象使得初学者可能不知道从哪里开始，如何选择内容，又该如何将其应用于特定需求。 本课程如何帮助您？ 本课程旨在简明并具实践性。我不打算覆盖所有的统计学、SPSS、数据分析和研究内容，这只会让学习之旅变得不必要地困难。相反，我将结构化地引导您，通过必要的知识和技能集来分析您的数据。尽管该课程不能让您成为统计、SPSS、数据分析和研究的专家，但它将帮助您完成自己的数据分析。具体实现方式如下： 1. 背景知识：课程每个部分都会简要介绍进行数据分析所需的基础统计概念。 2. 实践演示：所有视频都基于实例。在每个视频中，我会展示如何进行实际的数据分析任务，这些任务是从常见的分析中精心挑选的。 3. 经验分享：除了统计和SPSS，我还分享了很多我自己进行研究和数据分析的经验，包括如何处理在数据处理中常见的问题，避免常见的错误和误解，以及如何解决SPSS中的一些常见bug。 4. 重点提示：视频中突出关键点，并在每个视频结束时进行总结。 5. 练习：每个部分结束时都有一个练习，帮助您应用所学内容，另有问题促使您更深入思考操作内容。练习问题已经在我多年的线下课程中验证有效。 6. 参考文献：对于希望深入了解统计概念的学习者，我提供了有用的参考资料链接。 如何有效学习本课程？ 您可以按照以下步骤进行学习： 1. 观看视频，必要时做笔记。 2. 独立完成练习，仅知其然是不够的，必须付诸实践！ 3. 如果忘记一些细节，可以回顾之前的视频。 4. 进行练习后，观看下一个视频获取答案，仔细观察我的步骤并进行比较，思考哪种方法更优以及原因。 5. 最后，尝试将这些技术应用于您的实际数据中。 以上就是入门介绍，希望您学习愉快！
Thank you for checking in SPSS Data Analysis for Beginning Researchers.Who is this course for?As the title implies, this course is for people working on their very first research projects (i.e. beginners / newbies), including but not limited to:Students working on their research papers or dissertationsBeginning researchers with a non-technical backgroundAnyone curious about data analysisWhat is so difficult about data analysis?Many people find data analysis difficult, and with good reasons. Data analysis is difficult because it is not a single discipline. It is multi-disciplinary, which means that it requires integrated knowledge from different fields in order to do it right. Specifically, to conduct data analysis for your research you need:Knowledge in the data analysis software (e.g. SPSS, Excel, R, etc.)Knowledge in statistics conceptsKnowledge in research methodsExperience and skills working with dataWhat you need is not only knowledge in separate fields, but also experience and skills integrating these knowledge together to deal with real life data.However, beginning researchers, by definition, have very little of these knowledge, experience, and skills. For example:You may know how to use the data analysis software, but you don't know what method of analysis to use because you are not familiar with the statistics concepts.You may know some statistics, but you may not know how to calculate the statistics on the computer.You may have knowledge in both statistics and data analysis software, but you are not sure what analysis to conduct in order to fulfill the research needs.You may have knowledge in statistics, software, and research, but you may not have the experience in actually handling data, and you are stuck dealing with practical issues here and there (such as missing and invalid data).There are plenty of textbooks in these different disciplines, but few of them could teach you all these knowledge and skills. The problem is not lack of information. Quite the contrary, the problem is overwhelmingly rich information, so rich that you may not know where to start and how to select, so rich that you may not know how to put them into practice to fulfill your specific needs.How may this course help?This course is designed to be concise and practical. I am not attempting to tell you everything about statistics, SPSS, data analysis, and research - that would make your learning journey unnecessarily difficult. Instead, I am going to guide you, in an structured and practical way, through the minimal set of knowledge and skills you would need to analyze your own data. This course will not make you an expert in statistics, SPSS, data analysis, and research, but it will help you finish your own data analysis.This is to be achieved by the following:Background knowledge. Each section of the course begins with a brief introduction to the minimal set of necessary statistics concepts you need.Practical demonstrations. All the videos are example-based. In each video, I show you how to conduct a practical data analysis task. These tasks are carefully selected from a list of most common analyses that you are likely to conduct.Experience sharing. In addition to statistics and SPSS, I also share a lot of my own experience doing research and data analysis, including how to deal with the most common issues while working with data, avoid the common mistakes and misunderstandings, and work around some annoying bugs in SPSS.Key points. Key points are highlighted throughout the video and also recapped at the end of the videos.Exercise. There is an exercise at the end of each section. This helps you apply what you have learned in the previous videos. There are also questions that prompt you to think deeper about what you are doing. The exercise problems have been used for a few years in my own offline classes so they are proven to be helpful to students. While appropriate, a separate video is dedicated to demonstrating the answers to these exercise problems.References. For those who would like to dig deeper into the statistics concepts, I have included links to useful references for your pursue.So, how may I learn effectively in this course?You may do the following for each section:Watch the videos. Take notes while necessary.Complete the exercise on your own. Knowing is not enough. We must apply!If you forget some of the details, refer back to the previous videos.After attempting the exercise, watch the next video for answers. Watch my steps carefully and compare with yours. In case of any difference, ask yourself which way is better, and why.Last but not least, apply the techniques to your own data.That's all for the introduction. Happy learning!
