第11届全运会金牌的统计分析

文章主要运用文献资料等方法,对第11届全运会金牌的项目特征、区域特征以及性别特征等方面做一个全面的详细统计分析。结果表明,金牌的分布具有以下特征:1.前三名的省份(团体)的金牌总数占总金牌数的42.1%,是近5届占有比例最多的一届。2.竞技实力区域分布特征:华东地区最强;其次是实力相当的华北和东北地区;华南、华中和解体协仅次于华北和东北,再次是西南和西北地区,最弱是港澳地区。3.项目分布特征:项目的分布是不均匀的,表现出明显的区域优势和劣势特征,某一省份垄断某一项目的金牌是极其艰难的。4.性别特征:各个区域男女获得金牌数存在着男强女弱和男女相当两种倾向,具有代表性且金牌名次靠前的一些省份(团体)男女获得金牌数比例呈现男强女弱、男弱女强和男女相当三种倾向。旨在让大家更加理智客观的了解中国各个地区及省份(团体)的竞技实力,促进中国竞技体育全面可持续发展。     

CBA技术统计员临场统计要求与各项技术指标的标准和尺度

技术统计工作,是篮球竞赛组织工作中不可缺少的重要部分,其主要任务是力求准确全面地记录集体和个人在比赛中所表现出的各项技术数据,对篮球比赛和训练具有重要意义,是篮球科学训练与教学的常规工作。     

Student satisfaction with R vs. Excel in Data Mining and Business Analytics: A Herzberg's motivation-hygiene theory perspective

Applying Herzberg's motivation-hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators for student satisfaction with R would include: (i) an intrinsic interest in DMBA, (ii) a perception that R is a better tool than Excel for DMBA, and (iii) a favorable view of R as a facilitator of career advancement. We postulated that the hygiene factor was the compulsory course requirement to learn R, a new and challenging language to students in this study. Data from 120 students, analyzed using Principal Component Analysis (PCA) and Generalized Additive Modeling (GAM), showed that motivators were positively related to satisfaction while hygiene factors were neutral. Students showed willingness to take on a harder challenge in exchange for intrinsic and future career benefits. The model can be useful in curriculum design or career advisement to increase student satisfaction in learning new software skills while meeting market demands.     

Motivation for learning statistics: An example from fishery and aquaculture science

Teaching statistics to generalist students oriented toward a profession, rather than academic merits, may be challenging. As statistics courses also tend to have a low student appeal, tailoring a course toward this type of audience is demanding. Framed within the theory of statistical thinking and literacy, this article shows how an investigative process, using domain data and real-life examples, may facilitate meaningful learning and motivate students. Describing and reflecting upon the methods used, both in teaching and assessment, the article contributes to the practice of teaching statistics.     

Integrating the entrepreneurial mindset into solar energy statistical analysis and performance modeling

Statistical knowledge is required for students in a range of disciplines. However, there are limited educator resources that exist for applying statistics to solve real-world problems. This investigation provides one approach to teaching statistics using entrepreneurial-minded learning (as a way to connect real-world applications and value creation with problem-solving and curiosity) in the context of solar energy. Both the ready-to-use teaching intervention and assessment of student learning details are provided for an undergraduate course on Introductory Statistics. The teaching intervention includes a series of seven lesson plans (and three extension projects) that educators can use in an introductory statistics course.     

Exploring a complex gender wage gap dataset: an introductory activity in identifying issues and data visualization

In this paper, we provide instructors with an approach for a classroom activity for students in an introductory data science or statistics course who have little or no statistical programming experience. We designed this activity to help students improve their statistical literacy while exploring a social justice problem-the gender wage gap. To minimize the challenges of developing statistical literacy in students who lack programming skills, we developed a web-based data visualization application that does not require users to have any prior programming knowledge. The data in this visualization application comes from the March 2018 Current Population Uniform Extracts detailed by the Center for Economic Policy Research. Students can use the visualization application to create tables and plots to explore data on factors such as earnings and gender. Instructors can also use the application for other wage-related variables, such as race, occupation and family size.     

How learners produce data from text in classifying clickbait

Text provides a compelling example of unstructured data that can be used to motivate and explore classification problems. Challenges arise regarding the representation of features of text and student linkage between text representations as character strings and identification of features that embed connections with underlying phenomena. In order to observe how students reason with text data in scenarios designed to elicit certain aspects of the domain, we employed a task-based interview method using a structured protocol with six pairs of undergraduate students. Our goal was to shed light on students' understanding of text as data using a motivating task to classify headlines as “clickbait” or “news.” Three types of features (function, content, and form) surfaced, the majority from the first scenario. Our analysis of the interviews indicates that this sequence of activities engaged the participants in thinking at both the human-perception level and the computer-extraction level and conceptualizing connections between them.     

应用点阵笔技术 改进数学课堂教学---小学数学“统计与概率”教学实践的思考

新课标强调培养学生发现问题、提出问题、分析问题和解决问题的能力,这也是培养学生综合素质的关键。文章以“统计与概率”教学实践为例,对应用点阵笔技术改进数学课堂教学进行探究,以改变课堂教学生态,让数学课堂充满趣味性、探索性与创造性,激发学生学习兴趣,调动学生学习的积极性和主动性,培养学生发现问题、提出问题、分析问题和解决问题的能力。在教学中,教师要注重突出学生的主体地位,发挥学生的主体作用,促进学生思维发展。     

美国联邦政府R&D经费投入特点和变化趋势分析

首先介绍美国R&D经费的来源和执行者,分析美国R&D的投入特点和变化发展趋势;在此基础上详细解读美国联邦政府的R&D经费去向,并以合同预算和支出两套基础数据比较分析美国联邦政府四十多年R&D经费的变化发展特征,希望用于指导我国的R&D经费的管理与实践.