Teaching Ethics in a Statistics Curriculum with a Cross-Cultural Emphasis

Like most professional disciplines, the ASA has adopted ethical guidelines for its practitioners. To promote these guidelines, as well as to meet governmental and institutional mandates, U.S. universities are demanding more training on ethics within existing statistics graduate student curricula. Most of this training is based on the teachings of Western philosophers. However, many statistics graduate students are from Eastern cultures (particularly Chinese), and cultural and linguistic evidence indicates that Western ethics may be difficult to translate into the philosophical concepts common to students from different cultural backgrounds. This article describes how to teach cross-cultural ethics, with emphasis on the ASA Ethical Guidelines, within a graduate-level statistical consulting course. In particular, we present content that can help students overcome cultural and language barriers to gain an understanding of ethical decision-making that is compatible with both Western and Eastern philosophical models. Supplementary materials for this article are available online.     

Statistical Quality Control in the First Statistics Course

Articles regularly apppear in the “Teacher's Corner” of The American Statistician and elsewhere discussing which topics to include in the first statistics course, the order of presentation, and relative emphasis. The basic premise of this article is that some aspects of statistical quality control (SQC) should be incorporated into that first course. In brief, three points are made: (a) SQC concepts are not now widely taught; (b) they should be; and (c) it is relatively painless to do so.     

What Your Future Doctor Should Know About Statistics: Must-Include Topics for Introductory Undergraduate Biostatistics

The increased emphasis on evidence-based medicine creates a greater need for educating future physicians in the general domain of quantitative reasoning, probability, and statistics. Reflecting this trend, more medical schools now require applicants to have taken an undergraduate course in introductory statistics. Given the breadth of statistical applications, we should cover in that course certain essential topics that may not be covered in the more general introductory statistics course. In selecting and presenting such topics, we should bear in mind that doctors also need to communicate probabilistic concepts of risks and benefits to patients who are increasingly expected to be active participants in their own health care choices despite having no training in medicine or statistics. It is also important that interesting and relevant examples accompany the presentation, because the examples (rather than the details) are what students tend to retain years later. Here, we present a list of topics we cover in the introductory biostatistics course that may not be covered in the general introductory course. We also provide some of our favorite examples for discussing these topics.     

Ethical Numbers: Ethics Training in U.S. Graduate Statistics Programs, 2013–2014

As important members of research teams, statisticians bear an ethical responsibility to analyze, interpret, and report data honestly and objectively. One way of reinforcing ethical responsibilities is through required courses covering a variety of ethics-related topics at the graduate level. We assessed ethics requirements for graduate-level statistics training programs in the United States for the 2013–2014 academic year using the websites of 88 universities, examining 103 biostatistics programs, and 136 statistics degree programs. We categorized programs’ ethics training requirements as required or not required. Thirty-one (35.1%) universities required an ethics course for at least some degree students. Sixty-two (25.5%) degree programs required an ethics course for at least some students. The majority (77.4%) of required courses were worth 0 or 1 credit. Of the 177 programs without an ethics requirement, 19 (10.7%) listed an ethics elective. Although a single ethics course is insufficient for instilling an ethical approach to science, degree programs that model expectations through coursework point to the value of ethics in science. More training programs should prepare statisticians to consider the ethical dimensions of their work through required coursework. Supplementary materials for this article are available online.     

Statistics development: statistical methods meeting the user’s needs

Statistical methods have the potential of being effectively used by industrial practitioners if they satisfied two criteria: functionality and usability. Statistical methods are usually the product of statistical research activities of universities and other research organizations. Some already satisfy these criteria; however, many do not. The effect is that potentially relevant methods are not used in practice as often as they could be. In this paper we will present an approach regarding ‘statistics development,’ in which the end-user is given a central position, so that the results from statistical research aim to meet the needs and requirements of the practitioner. Examples of known and new methods will be presented, and we will discuss issues such as education in statistics, the link with statistical consultancy and publication of methods through various channels.     

Statistics in the elementary school

This paper discusses the role of statistics within an interdisciplinary program on real problem solving in elementary schools (through grade 8). We first describe some general features of the USMES (Unified Science and Mathematics for Elementary Schools) curriculum and some situations where the application of statistical principles and techniques can enter the program. Then we present our ideas concerning the kinds of statistical methods that are appropriate in this environment, and we discuss the use of this material with both elementary school students and elementary     

Teaching Statistics Theory through Applications

This article presents a model for developing case studies, or labs, for use in undergraduate mathematical statistics courses. The model proposed here is to design labs that are more in-depth than most examples in statistical texts by providing rich background material, investigations and analyses in the context of a scientific problem, and detailed theoretical development within the lab. An important goal of this approach is to encourage and develop statistical thinking. It is also advocated that the labs be made the centerpiece of the theoretical course. As a result, the curriculum, lectures, and assignments are significantly restructured. For example, the course work includes written assignments based on open-ended data analyses, and the lectures include group work and discussions of the case-studies.     

The Religion of Statistics as Practiced in Medical Journals

Commentaries are informative essays dealing with viewpoints of statistical practice, statistical education, and other topics considered to be of general interest to the broad readership of The American Statistician. Commentaries are similar in spirit to Letters to the Editor, but they involve longer discussions of background, issues, and perspectives. All commentaries will be refereed for their merit and compatibility with these criteria.

The way in which hypothesis tests are often used as the sole tool of statistics in medical research is satirized. This is followed by a suggestion for reform.     

131st Annual Meeting Joint Statistical Meetings of the American Statistical Association,The Blometrlc Society,Enar and Wnar,The Institute of Mathematical Statistics

(We are attempting to inaugurate a different type of questions and answers page in this issue of the American Statistician. Our purpose is to stimulate an interest in conceptual and measurement problems which arise in the course of statistical work and which require discussion apart from purely mathematical considerations. It is hoped that our readers will find this approach of interest and value. We are inviting questions of this type.)     

Major League Baseball Player Salaries: Bringing Realism into Introductory Statistics Courses

A dataset consisting of salaries of major league baseball players is published at the start of each season in USA Today, and is also made available on the Internet. It is argued that such an easily available dataset and those similar to it can be successfully used by students in a first statistics course for an interesting introduction to data analysis through summary measures and graphical displays. Such an approach is most natural for many students because of a strong interest in sports and economics. Other statistical ideas can be explored as a natural consequence of the discussions that ensue from such an analysis.     

大数据与统计新思维

最近,《大数据时代》等几本书引起了广泛的关注,大数据正在改变着人们的行为与思维,那么以数据为研究对象的统计学该如何应对？本文基于对大数据的理解,认为统计思维需要发生三个方面的改变：即认识数据的思维、收集数据的思维和分析数据的思维要改变。其中,数据分析思维又要在统计分析过程、实证分析思路、推断分析逻辑等方面发生变化,同时统计分析评价的标准也要有所调整。围绕这些变化,本文提出需要从八个方面去积极应对大数据,以促使统计学科跟上时代的步伐。     

Graduate Statistics Service Courses

This article describes our experience in, and recommendations for, teaching introductory statistics service courses to graduate students. Drawing on the student's research orientation, the instructor can present statistics as a valuable component of the scientific method, using examples from the student's particular discipline(s). Statistically qualified course instructors may be affiliated with statistics or other departments, and the course may be offered within any department. Course goals can range from training students to function independently as statistical analysts in future research to training students to consult a qualified statistician about design and analysis issues.     

Are Overall Journal Rankings a Good Mapping for Article Quality in Specialty Fields?

Overall journal rankings, which are generated with sample articles in different research fields, are commonly used to measure the research productivity of academic economists. In this article, we investigate a growing concern in the profession that the use of the overall journal rankings to evaluate scholars’ relative research productivity may exhibit a downward bias toward researchers in some specialty fields if their respective field journals are under-ranked in the overall journals rankings. To address this concern, we constructed new journal rankings based on the intellectual influence of research in 8 specialty fields using a sample consisting of 26,401 articles published across 60 economics journals from 1998 to 2007. We made various comparisons between the newly constructed journal rankings in specialty fields and the traditional overall journal ranking. Our results show that the overall journal ranking provides a considerably good mapping for the article quality in specialty fields. Supplementary materials for this article are available online.     

Content Audit for p-value Principles in Introductory Statistics

ABSTRACT

Longstanding concerns with the role and interpretation of p-values in statistical practice prompted the American Statistical Association (ASA) to make a statement on p-values. The ASA statement spurred a flurry of responses and discussions by statisticians, with many wondering about the steps necessary to expand the adoption of these principles. Introductory statistics classrooms are key locations to introduce and emphasize the nuance related to p-values; in part because they engrain appropriate analysis choices at the earliest stages of statistics education, and also because they reach the broadest group of students. We propose a framework for statistics departments to conduct a content audit for p-value principles in their introductory curriculum. We then discuss the process and results from applying this course audit framework within our own statistics department. We also recommend meeting with client departments as a complement to the course audit. Discussions about analyses and practices common to particular fields can help to evaluate if our service courses are meeting the needs of client departments and to identify what is needed in our introductory courses to combat the misunderstanding and future misuse of p-values.     

经济、管理类专业《统计学》课程建设的几个基本问题

内容提要：本人认为,目前在我国经济、管理类专业《统计学》课程建设中尚有一些基本理论问题需要讨论清楚。例如,怎样理解“统计学是一门数据科学”这一命题,以及课程改革后的《统计学》与改革前的《社会经济统计学原理》究竟有什么本质上的区别;《统计学》课程中用于对重复随机试验进行统计推断的样本和抽样调查中的样本有什么区别和联系;应用社会经济调查数据进行统计分析较之应用实验数据进行统计分析有什么特殊性的问题需要解决,等等。文章找出了这些问题的若干误区并阐述了作者的个人见解。     

Statistics in seismology

A range of problems in the applications of statistics to seismology is surveyed. In each case, brief notes are provided on the seismological background to the problem, the essential character of the statistical questions which arise, some key references, and the direction of current work. Two broad sections are included, the first covering the analysis of raw data from the seismogram traces, the second covering the analysis of derived data such as lists of earthquake epicentres and magnitudes.     

The Use of Investigations in the Introductory Statistics Course

Reasons for including investigations in a first course in statistics are presented. Investigations create an environment of participation and give the student the opportunity to experience statistics in action. This participation highlights the interaction between science and statistics. Suggestions are made regarding the integration of investigations into a formal course environment. One investigation is presented in detail. Thirteen other investigations are outlined. Emphasis is placed on experiments that require minimal set-up time yet illustrate important statistical concepts.     

财经院校统计学双语教学实践研究

本文通过对统计学双语教学实践的研究和探讨,指出在高等财经院校开展统计学双语,有利于培养符合经济发展的高素质人才,并有助于统计学本学科自身的发展。结合教学的实践,提出了统计学双语教学的实践方法。     

Quality control procedures at statistics sweden

This paper treats quality control in a wide sense which is imperative for a statistical agencyto do. First, we discuss the meaning of total survey error and different quality characteris-

tics. Secondly, some common quality problems in statistical agencies are presented as a prelude to the bulk of this paper, namely the case of Sweden. Quality control efforts at Statistics Sweden are reviewed regarding the handling of specific error sources, error estimation, and error control. Different tools such as preventive control, production control, and evaluation are dealt with. As for QC-procedures proper we provide some applications from clerical coding.