医学统计学与SPSS软件（基础篇）

Peking University via Coursera

Go to Course: https://www.coursera.org/learn/spss-ruanjian

Introduction

**Course Review: 医学统计学与SPSS软件（基础篇） on Coursera** **Overview:** The course titled 医学统计学与SPSS软件（基础篇), translated as "Medical Statistics and SPSS Software (Basic Version)," offers a comprehensive introduction to statistical methods specifically tailored for students from various medical disciplines and healthcare professionals. It covers fundamental statistical concepts and the application of SPSS software through a structured curriculum. The course aims to equip learners with essential statistical analysis skills, fostering statistical thinking that can be applied effectively in medical research. **Syllabus Breakdown:** The course spans six weeks, each focusing on vital statistical topics and associated SPSS software usage: 1. **Week 1 - Introduction:** - Focuses on basic concepts like populations, samples, small probability events, and data types. - Introduces SPSS data management functions, including sorting and recoding, allowing students to become adept at organizing their data. 2. **Week 2 - Statistical Description:** - Covers measures of central tendency and dispersion, emphasizing their applications. - Teaches the differences between rates and proportions while ensuring proficiency in SPSS for performing statistical descriptions. 3. **Week 3 - Hypothesis Testing for Two Groups:** - Introduces the concepts of sampling error and confidence intervals. - Detailed instruction on independent sample t-tests and paired t-tests is provided, focusing on potential errors and statistical power, backed up with hands-on SPSS exercises. 4. **Week 4 - Hypothesis Testing for Multiple Groups:** - Explains fundamental concepts of Analysis of Variance (ANOVA). - Practical understanding of completely randomized designs and randomized block designs are developed through SPSS software. 5. **Week 5 - Hypothesis Testing for Categorical Variables:** - Discusses sampling error and confidence intervals for rates. - Teaches chi-squared tests for independent samples and paired designs, with SPSS exercises for enhanced learning. 6. **Week 6 - Linear Regression and Correlation:** - Covers linear regression analysis, hypothesis testing, and applicable conditions. - Distinguishes between linear regression and correlation, culminating in practical SPSS applications. 7. **Final Examination:** - A comprehensive assessment of all the topics covered in the course. **Review:** The course is exceptionally well-structured, demonstrating a detailed balance of theory and practical application. Each module builds upon the previous one, gradually enhancing the learner’s understanding of both statistics and SPSS. The inclusion of real-world applications in a medical context ensures that the course remains relevant and practical for healthcare professionals. The blend of statistical theory with hands-on software training makes it suitable not only for medical students but also for healthcare workers looking to refine their data analysis skills. The course teaches rigorous methodological skills that are crucial in conducting valid research in medicine. **Recommendation:** I highly recommend 医学统计学与SPSS软件（基础篇） for anyone pursuing a career in healthcare or medical research. It is particularly beneficial for those looking to improve their statistical analysis skills and become adept at using SPSS. The course content is robust, the teaching materials are accessible, and the skills gained will undoubtedly enhance one’s capacity to perform meaningful medical research. If you are seeking to build a solid foundation in medical statistics that is directly applicable to your career, this course is an excellent choice. Enroll today to start mastering the essential techniques of medical statistics and SPSS software!

Syllabus

第一周 绪论

本周学习重点：1.重点掌握以下基本概念：总体、样本、小概率事件、资料的类型。2.熟练掌握SPSS软件基本数据管理功能：排序、拆分、选择、计算、重新编码。

第二周 统计描述

本周学习重点：1.重点掌握集中趋势与离散趋势指标的适用条件。 2.重点掌握率与比例在实际应用中的区别。 3.熟练掌握SPSS软件的统计描述操作。

第三周 两组数值变量比较的假设检验

本周学习重点：1.重点掌握以下基本概念：均数的抽样误差与总体均数的置信区间。 2.理解假设检验的基本原理。 3.重点掌握独立样本比较的t检验、配对设计t检验。 4.重点掌握两类错误、功效的基本概念。 5.熟练掌握t检验的SPSS软件操作及结果解释。

第四周 多组数值变量比较的假设检验

本周学习重点：1.理解方差分析的基本思想。2.重点掌握完全随机设计、随机区组设计的方差分析。3.熟练掌握方差分析的SPSS软件操作及结果解释。

第五周 分类变量比较的假设检验

本周学习重点：1.重点掌握以下基本概念：率的抽样误差与总体率的置信区间。 2.重点掌握独立样本、配对设计四格表资料的卡方检验。 3.熟练掌握卡方检验的SPSS软件操作及结果解释。

第六周 直线回归与相关

本周学习重点：1.重点掌握直线回归方程的估计、假设检验、适用条件。 2.重点掌握直线相关系数的估计、假设检验。 3.重点理解直线回归与相关的区别、联系。 4.熟练掌握直线回归与相关的SPSS软件操作及结果解释。

期末考试