Pub Date : 2020-12-01DOI: 10.1080/10691898.2020.1854638
L. C. Pyott
{"title":"Tennis Anyone? Teaching Experimental Design by Designing and Executing a Tennis Ball Experiment","authors":"L. C. Pyott","doi":"10.1080/10691898.2020.1854638","DOIUrl":"https://doi.org/10.1080/10691898.2020.1854638","url":null,"abstract":"","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1854638","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43610464","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}
Pub Date : 2020-11-17DOI: 10.1080/10691898.2020.1850220
Alaa M. Althubaiti
{"title":"Attitudes of Medical Students Toward Statistics in Medical Research: Evidence From Saudi Arabia","authors":"Alaa M. Althubaiti","doi":"10.1080/10691898.2020.1850220","DOIUrl":"https://doi.org/10.1080/10691898.2020.1850220","url":null,"abstract":"","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1850220","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59859624","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}
Pub Date : 2020-11-03DOI: 10.1080/10691898.2020.1844104
Nicolas Christou
{"title":"Spatial Data in Undergraduate Statistics Curriculum","authors":"Nicolas Christou","doi":"10.1080/10691898.2020.1844104","DOIUrl":"https://doi.org/10.1080/10691898.2020.1844104","url":null,"abstract":"","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1844104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47302459","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}
Pub Date : 2020-10-29DOI: 10.1080/10691898.2020.1844105
Lynette M. Smith, Fang Yu, K. Schmid
Replication and reproducibility are an important component of scientific research. One reason research is not replicable is the misuse of statistical techniques. Educators can teach the importance ...
{"title":"Role of Replication Research in Biostatistics Graduate Education","authors":"Lynette M. Smith, Fang Yu, K. Schmid","doi":"10.1080/10691898.2020.1844105","DOIUrl":"https://doi.org/10.1080/10691898.2020.1844105","url":null,"abstract":"Replication and reproducibility are an important component of scientific research. One reason research is not replicable is the misuse of statistical techniques. Educators can teach the importance ...","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1844105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45267980","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}
Pub Date : 2020-10-26DOI: 10.1080/10691898.2020.1841592
H. Hoffman, A. Elmi
Our study compared the performance of students enrolled in a graduate-level introductory biostatistics course in an online versus a traditional in-person learning environment at a school of public ...
我们的研究比较了在一所公立学校参加在线生物统计学入门课程的学生和传统的面对面学习环境的学生的表现。
{"title":"Comparing Student Performance in a Graduate-Level Introductory Biostatistics Course Using an Online versus a Traditional in-Person Learning Environment","authors":"H. Hoffman, A. Elmi","doi":"10.1080/10691898.2020.1841592","DOIUrl":"https://doi.org/10.1080/10691898.2020.1841592","url":null,"abstract":"Our study compared the performance of students enrolled in a graduate-level introductory biostatistics course in an online versus a traditional in-person learning environment at a school of public ...","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1841592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48419825","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}
Pub Date : 2020-09-01DOI: 10.1080/10691898.2020.1841589
John K. Burke, Levon Goukasian, Robert Shearer
Abstract Students often struggle with the concept of dependence of events or random variables. We present a simple coin flipping game that yields surprising results due to the dependencies within the game. The game is simple enough for young children to understand and play, yet complex enough to yield results that are counterintuitive to even most graduate students. We discuss how to implement the game in a classroom, suggest two problems from the game for students to solve, and present several solutions to the problems.
{"title":"Teaching the Complexity of Dependence With the Triplet Game","authors":"John K. Burke, Levon Goukasian, Robert Shearer","doi":"10.1080/10691898.2020.1841589","DOIUrl":"https://doi.org/10.1080/10691898.2020.1841589","url":null,"abstract":"Abstract Students often struggle with the concept of dependence of events or random variables. We present a simple coin flipping game that yields surprising results due to the dependencies within the game. The game is simple enough for young children to understand and play, yet complex enough to yield results that are counterintuitive to even most graduate students. We discuss how to implement the game in a classroom, suggest two problems from the game for students to solve, and present several solutions to the problems.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1841589","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48737796","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}
Pub Date : 2020-09-01DOI: 10.1080/10691898.2020.1841591
A. Hoegh
Abstract While computing has become an important part of the statistics field, course offerings are still influenced by a legacy of mathematically centric thinking. Due to this legacy, Bayesian ideas are not required for undergraduate degrees and have largely been taught at the graduate level; however, with recent advances in software and emphasis on computational thinking, Bayesian ideas are more accessible. Statistics curricula need to continue to evolve and students at all levels should be taught Bayesian thinking. This article advocates for adding Bayesian ideas for three groups of students: intro-statistics students, undergraduate statistics majors, and graduate student scientists; and furthermore, provides guidance and materials for creating Bayesian-themed courses for these audiences. Supplementary files for this article are available on line.
{"title":"Why Bayesian Ideas Should Be Introduced in the Statistics Curricula and How to Do So","authors":"A. Hoegh","doi":"10.1080/10691898.2020.1841591","DOIUrl":"https://doi.org/10.1080/10691898.2020.1841591","url":null,"abstract":"Abstract While computing has become an important part of the statistics field, course offerings are still influenced by a legacy of mathematically centric thinking. Due to this legacy, Bayesian ideas are not required for undergraduate degrees and have largely been taught at the graduate level; however, with recent advances in software and emphasis on computational thinking, Bayesian ideas are more accessible. Statistics curricula need to continue to evolve and students at all levels should be taught Bayesian thinking. This article advocates for adding Bayesian ideas for three groups of students: intro-statistics students, undergraduate statistics majors, and graduate student scientists; and furthermore, provides guidance and materials for creating Bayesian-themed courses for these audiences. Supplementary files for this article are available on line.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1841591","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45644570","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}
Pub Date : 2020-09-01DOI: 10.1080/10691898.2020.1807429
E. Latif, Stan Miles
Abstract Using data on students at a Canadian business school, this article studies the effect of homework assignments and in-class quizzes on exam performance. Based on a difference-in-difference approach, assignments had a statistically discernible positive impact on exam grades for the overall sample. When broken down by gender, assignments had a positive impact on exam grades for males but no statistically discernible impact for females. Quizzes had no statistically discernible impact overall or for either gender. When broken down by student residency status, both assignments and quizzes positively impacted exam grades for international students, but there was no statistically discernible impact of assignments or quizzes for domestic students.
{"title":"The Impact of Assignments and Quizzes on Exam Grades: A Difference-in-Difference Approach","authors":"E. Latif, Stan Miles","doi":"10.1080/10691898.2020.1807429","DOIUrl":"https://doi.org/10.1080/10691898.2020.1807429","url":null,"abstract":"Abstract Using data on students at a Canadian business school, this article studies the effect of homework assignments and in-class quizzes on exam performance. Based on a difference-in-difference approach, assignments had a statistically discernible positive impact on exam grades for the overall sample. When broken down by gender, assignments had a positive impact on exam grades for males but no statistically discernible impact for females. Quizzes had no statistically discernible impact overall or for either gender. When broken down by student residency status, both assignments and quizzes positively impacted exam grades for international students, but there was no statistically discernible impact of assignments or quizzes for domestic students.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1807429","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43816951","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}
Pub Date : 2020-09-01DOI: 10.1080/10691898.2020.1837039
Anna-Marie Fergusson, M. Pfannkuch
Abstract Informally testing the fit of a probability distribution model is educationally a desirable precursor to formal methods for senior secondary school students. Limited research on how to teach such an informal approach, lack of statistically sound criteria to enable drawing of conclusions, as well as New Zealand assessment requirements led to this study. Focusing on the Poisson distribution, the criteria used by ten Grade 12 teachers for informally testing the fit of a probability distribution model was investigated using an online task-based interview procedure. It was found that criteria currently used by the teachers were unreliable as they could not correctly assess model fit, in particular, sample size was not taken into account. The teachers then used an interactive goodness of fit simulation-based visual inference tool (GFVIT) developed by the first author to determine if the teachers developed any new understandings about goodness of fit. After using GFVIT teachers reported a deeper understanding of model fit and that the tool had allowed them to take into account sample size when testing the fit of the probability distribution model through the visualization of expected distributional shape variation. Hence, a new informal test for the fit of a probability distribution is proposed.
{"title":"Development of an Informal Test for the Fit of a Probability Distribution Model for Teaching","authors":"Anna-Marie Fergusson, M. Pfannkuch","doi":"10.1080/10691898.2020.1837039","DOIUrl":"https://doi.org/10.1080/10691898.2020.1837039","url":null,"abstract":"Abstract Informally testing the fit of a probability distribution model is educationally a desirable precursor to formal methods for senior secondary school students. Limited research on how to teach such an informal approach, lack of statistically sound criteria to enable drawing of conclusions, as well as New Zealand assessment requirements led to this study. Focusing on the Poisson distribution, the criteria used by ten Grade 12 teachers for informally testing the fit of a probability distribution model was investigated using an online task-based interview procedure. It was found that criteria currently used by the teachers were unreliable as they could not correctly assess model fit, in particular, sample size was not taken into account. The teachers then used an interactive goodness of fit simulation-based visual inference tool (GFVIT) developed by the first author to determine if the teachers developed any new understandings about goodness of fit. After using GFVIT teachers reported a deeper understanding of model fit and that the tool had allowed them to take into account sample size when testing the fit of the probability distribution model through the visualization of expected distributional shape variation. Hence, a new informal test for the fit of a probability distribution is proposed.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1837039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43138886","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}
Pub Date : 2020-09-01DOI: 10.1080/10691898.2020.1854598
W. Jeff
{"title":"Note from the Editor","authors":"W. Jeff","doi":"10.1080/10691898.2020.1854598","DOIUrl":"https://doi.org/10.1080/10691898.2020.1854598","url":null,"abstract":"","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1854598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44357828","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}
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