Sports Statistics and SPSS Case Analysis

Course Nature and Importance

    Sports Statistics is a foundational applied discipline that uses the principles and methods of mathematical statistics to study the "regularities" of various random phenomena in the field of sports. It is an essential methodological subject for the training of undergraduate and graduate students in sports programs, and an important content for ordinary grassroots workers who need to analyze data or write research reports.

Purpose of the Course

    In nearly 20 years of teaching this course, I have experienced the evolution from purely teaching sports statistics theory to delivering software in “full English version” to “full Chinese version.” Due to reasons such as sports students’ weak English proficiency and basic math foundation, many difficulties and insurmountable obstacles have been encountered. After accumulating much experience, I finally found a path that makes it easier for students to learn and apply the course theory and software. Therefore, this method is shared with many learners who have weak math foundations and tend to be deterred by the complexity of statistical principles, formulas, and calculation processes.

    Another reason for offering this course is that, after continuous upgrades to the Chinese version of SPSS software, its functionality has become very powerful, and the interface more user-friendly, making it more accessible to many researchers. While this is good news, there have been some undesirable outcomes, such as many graduate students blindly using SPSS software without considering their field of study, objective reality, or statistical principles. This often results in the misuse of statistical methods, presentation of flashy but irrelevant statistical data, and incorrect statistical conclusions. The aim of this course is to help learners establish a common understanding of scientific research, avoid statistical misconceptions, and foster multidimensional discussions and interactions between students during class and on the learning platform. This collaborative support will ultimately reduce the "misuse of statistical methods" and "lack of practical research."

Course Overview
The course is divided into nine sessions, featuring 28 carefully selected cases, and is paired with IBM’s SPSS software for practical teaching.

The overall course design is completed by Mu Shunbi. Gao Chugang teaches five cases (Sessions 8, 9, 10, 12, 20), and Yang Yong teaches three cases (Sessions 13, 14, 15). The remaining 20 cases are taught by Mu Shunbi.

Course Features
Target Audience
This course is primarily designed for learners who lack a solid foundation in mathematics, are unfamiliar with the theoretical depth of statistics, fear the complexities of calculations, lack the mental energy for extensive study, but need to apply statistical methods in their graduation thesis or scientific research. The course distills extensive statistical theories and SPSS software operations into "refined" and "reconstructed" knowledge, fully considering the learners' characteristics and needs. It starts with "practical problems" and designs "cases" around them, emphasizing the course's applicability, practicality, and relevance, providing effective solutions to problems encountered in scientific research.

Content Design
The course’s knowledge points are designed to be "small but refined," relatively independent, yet logically structured. It emphasizes the characteristics of "concise yet comprehensive, fragmented yet connected, abundant yet organized." The course is designed with the learner's needs in mind, offering flexible learning options. Learners can choose content based on "titles," use "scattered time" to study individual cases, or explore topics of interest in their "leisure time". For larger chunks of time, learners can follow the structured sequence and study a series of related cases as "major units." This flexible structure ensures learners can learn efficiently and apply knowledge practically.

Integration of Knowledge Areas
The course integrates "statistical theory," "SPSS software functionality," "sports practice," "sports science research," and "statistical methods" into a "closed loop," using "cases" to consolidate interdisciplinary connections. Through video reviews, reinforcement, and in- and outside-class interaction, we aim to establish a "multi-disciplinary, single-discipline depth, and rotating integration" learning space. The goal is to master statistical principles while enabling learners to quickly apply these principles through software to analyze and solve "practical problems" and validate the logical relationships between issues to achieve scientific research goals. As such, the course has strong connections, adaptability, and integration with SPSS software, sports practice, and sports science research, making it suitable for researchers at the beginner, intermediate, and advanced levels.