Teaching Statistics最新文献

{"title":"Issue Information","authors":"","doi":"10.1111/test.12268","DOIUrl":"https://doi.org/10.1111/test.12268","url":null,"abstract":"","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45745776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"16th Conference of The Mathematics Education for the Future Project: Building on the Past to Prepare for the Future, King's College, Cambridge University, UK, Aug 8‐13, 2022","authors":"","doi":"10.1111/test.12294","DOIUrl":"https://doi.org/10.1111/test.12294","url":null,"abstract":"","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42128766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical meaningfulness, teaching craft and writing about teaching statistics and data science","authors":"H. MacGillivray","doi":"10.1111/test.12300","DOIUrl":"https://doi.org/10.1111/test.12300","url":null,"abstract":"In this issue we celebrate the awarding of three prizes for papers on good practice in teaching statistics and data science: the C Oswald George prize for best paper in Teaching Statistics issues 1 to 3 in 2021; the Peter Holmes prize for highlighting excellence in motivating practical classroom activity in these issues; and the Teaching Statistics Trust prize for best paper in the 2021 special issue on Teaching Data Science and Statistics. The announcements and citations for these three papers may be found in this issue. These papers significantly add to the demonstration of the work across the world in developing, implementing, sustaining and researching good practice in teaching statistics and data science, and this issue also includes editorial thanks and appreciation to all who contribute to the writing on such good practice authors, reviewers, the Teaching Statistics Trust and publisher Wiley. There is substantial need for, and considerable appreciation of, more writing of high standard on good practice in teaching statistics and data science. Full text downloads of papers in Teaching Statistics increased by approximately 30% from 2016 to 2020, but increased again by more than 33% in just the first 10 months of 2021 with the addition of the special issue. There is also need for a substantial cultural shift with greater acknowledgement and respect for the skills and expertise required for good teaching of statistics and data science in and across all disciplines, especially foundation and introductory, and for creditable and refereed writing on good practice in such teaching in its development, implementation, sustainment, evaluation and research. Hence there is need for understanding of both what constitutes good practice in teaching statistics and data science, and what constitutes good writing and researching such practice. Although there has been much discussion over the past three decades on the former, this discussion must be ongoing and constantly evolve to reflect the constantly evolving and dynamic nature of statistics and data science as they develop diverse capabilities (methodological, conceptual, and technological) to tackle increasingly complex and large problems in wideranging real contexts. Clearly the first requirement of the latter is that it must be about good practice in the teaching. However it should also satisfy criteria of scholarly writing but appropriate for the very large community of all those who teach statistics and data science. In the interests of reader convenience, I am now going to use the word “statistics” instead of “statistics and data science” to include everything to do with thought, endeavours and professional practice involving chance, variation and data, without attempting to describe any internal or external possible “boundaries”. There has been much emphasis over many decades that good statistics teaching must reflect the good practice of statistics, but the parallels between the two are far deepe","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48971998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Peter Holmes Prize Announcement 2021","authors":"H. MacGillivray","doi":"10.1111/test.12297","DOIUrl":"https://doi.org/10.1111/test.12297","url":null,"abstract":"The article entitled “Discovering experimental design: An interactive teaching exercise using Fisher’s tea-tasting experiment” by Thomas Fanshawe has been awarded the Peter Holmes prize for 2021. The aim of this prize is to highlight excellence in motivating practical classroom activity. This article describes using a classic experiment in an active learning, student discovery preliminary to experimental design in an introductory medical statistics module whose aim is for students to gain an understanding of statistics applied to biomedical science. It is written extremely clearly but succinctly, with pleasing historical context and details invaluable to anyone using a student discovery approach in a time-poor course in another discipline, especially professional disciplines with students demanding usefulness and engagement but also efficient use of time. The summary of student group designs, of small but important changes made based on student feedback, and practical tips for consistency in teaching approaches are as helpful as they are clear. The author’s comments such as “The diverging opinions that arose over design choices were a microcosm of discussions that arise when designing real-life experimental studies” are both interesting and useful. This concise but well-planned learning experience provided a useful foundation for a later class dedicated to medical study design, and opportunities to learn points relating to the connection between design and analysis. However the exercise is readily amenable to adaptation for students at different levels of education and ability. Overall, this article embodies the aim and spirit of the Peter Holmes prize in an excellent demonstration of a practical and fun classroom activity, embodying authentic student discovery practice within a design environment. Congratulations to the author for this excellent paper. 1 | HISTORY OF THE PRIZE","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49050454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using a video presentation on variance and covariance in the teaching of statistics","authors":"Kim L. Austerschmidt, Alexander Stappert, Hanna Heusel, Sarah Bebermeier","doi":"10.1111/test.12292","DOIUrl":"https://doi.org/10.1111/test.12292","url":null,"abstract":"We outline the use and evaluation of a video presentation about variance and covariance developed to motivate students to process the topics and to enhance their skills. We outline the structure and the content of the video presentation and present data of an evaluation study. Students in different subjects who must pass statistics courses (N = 114) participated in an online survey with randomized controlled design and repeated measurement. Results indicate that students who watched the video presentation significantly improved on their skills, compared to a control group reading a textbook section about the same topics. The video presentation was judged as more satisfying and useful for learning than the text. We discuss application scenarios and further teaching implications. Ideally a longitudinal study should investigate effects of continuous learning with video presentations, changes in motivation, anxiety, and attitudes as well as effects for students of different subjects.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"44 1","pages":"15 - 20"},"PeriodicalIF":0.8,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47878658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Take a chance on statistical edutainment","authors":"L. Lesser, D. Pearl","doi":"10.1111/test.12293","DOIUrl":"https://doi.org/10.1111/test.12293","url":null,"abstract":"Chances are that edutainment fun items can engage students in discussing and learning key concepts about probability.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"44 1","pages":"34 - 42"},"PeriodicalIF":0.8,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43219085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data visualization in introductory business statistics to strengthen students' practical skills","authors":"J. L. Hsu, Abram J. Jones, Jia-Huei Lin, You-Ren Chen","doi":"10.1111/test.12291","DOIUrl":"https://doi.org/10.1111/test.12291","url":null,"abstract":"The objective of this study is to present and discuss how data visualization can be incorporated into teaching approaches by business faculty in introductory business statistics to strengthen business students' practical skills. Data visualization lessens difficulties in learning statistics by providing opportunities to illustrate analytical findings in graphic form, which is essential for learners with different learning styles. Familiarizing students with Excel, Python, or other software in introductory business statistics is beneficial in helping them attain statistical literacy by analyzing real‐world data such as COVID‐19 statistics. Using such data equips students with knowledge of statistical implementation—a core skill in the business world.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"44 1","pages":"21 - 28"},"PeriodicalIF":0.8,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46523514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving the students' learning process through the use of statistical applets","authors":"A. Variyath, Tharshanna Nadarajah","doi":"10.1111/test.12290","DOIUrl":"https://doi.org/10.1111/test.12290","url":null,"abstract":"Undergraduate statistics teaching has always faced the challenge of improving the learning quality on a continuous basis. Interactive statistical applets can enhance statistical knowledge by providing multiple representations of basic concepts and facilitating experimentation. The use of these applets will simplify the efforts for teaching statistics, especially in convincing students of the usability of statistics and facilitating quick learning in undergraduate courses. We developed and implemented a set of web‐based statistical applets from the following areas: Basic Statistics, Coin Toss App, Scatterplot‐Regression Line, Standard Normal Distribution, Normal Distribution, Histogram, Histogram (Case Examples), and Sampling ‐ Canada Map. These interactive applets can perform specific statistical tasks to improve the students' learning process.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"44 1","pages":"14 - 5"},"PeriodicalIF":0.8,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43666740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is there a right way round?","authors":"H. MacGillivray","doi":"10.1111/test.12288","DOIUrl":"https://doi.org/10.1111/test.12288","url":null,"abstract":"At the recent OZCOTS (Australian Conference on Teaching Statistics), https://anzsc2021.com.au/ozcots-conference/, Rob Gould's keynote, titled Data Education in pre-College: promises and challenges, attracted a question from Matthew Parry, University of Otago, as to whether the scenario of “.. here's a bunch of data, come up with questions..” is a type of reversal of much previous advocacy to source or collect data to investigate identified issues. Rob's reply, and his discussion in his 2021 paper “Towards data-scientific thinking” [1], include comments that whatever codification is used for the statistical investigation cycle, now often called the data cycle or the learning from data cycle “...it is expected that investigators will ‘skip around' to some extent.” and that the order is not strict. This can be seen in examination of a variety of statistical and data investigations in real and complex contexts, whether in research or applications. In References [1,3], both Rob Gould and Andee Rubin emphasize “consider data” to include all aspects of the assembly of data, whether the data is assembled through sourcing, searching, collating or collecting, or is already available. They, and other authors, comment that the deluge of data means that students and indeed investigators more and more consider or access data already collected. Technological advances also enable greater and more ready access to collected data, and the necessary wrangling to handle such data. These in turn open up many possibilities for students to explore civic issues, including the critiquing of data with the associated vital learning about data quality and inherent dangers in uncritical algorithmic approaches. Rob also commented that students seem to find difficulty in identifying what statistical questions can be posed for an existing dataset. It is interesting to consider that today's data deluges require a return to more emphasis on the questions of “what, when, how, why, who?” In previous eras when instructors had no choice but to provide data and their context to students, these questions were of paramount importance in authentic statistical learning. For those in workplaces, not being able to find answers to such dataquerying questions, prevented the critiquing of reports or the building on previous data investigations or the redoing of analyses. As access to technology increased, enabling students to explore and analyse data beyond simplistic pocket calculator restrictions, students were able to design, collect, observe or source their own data to investigate issues involving a number of variables of interest to them. This could also introduce another question of great practical importance in many disciplines and workplaces, namely, can we measure what we want to measure? Including the information on the “what, when, why, how” in their reporting of data investigations, was, and is, excellent grounding for their future work whether in industry, business or research. Hen","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/test.12288","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49148346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Issue Information","authors":"","doi":"10.1111/test.12227","DOIUrl":"https://doi.org/10.1111/test.12227","url":null,"abstract":"","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/test.12227","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48327877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}