Pub Date : 2023-01-02DOI: 10.1080/09332480.2023.2179274
M. Risser, Steve Pierson
Abstract This article describes the work of the American Statistical Association (ASA) Advisory Committee on Climate Change Policy (ACCP) which was established in 2008. The committee’s earliest activities included meetings with Congressional committee staffers to hear firsthand their views on climate change, how or whether it should be addressed, and how the statistical perspective may be helpful. Building on the successes in raising awareness on Capitol Hill and beyond regarding the reality of climate change, the group is now pivoting to an emphasis on promoting solutions to climate change. These new efforts will ultimately enable statisticians and data scientists to engage more deeply in the research that is critical to society proactively and successfully addressing the intensifying impacts of climate change.
{"title":"Advisory Committee on Climate Change Policy: A Committee of the American Statistical Association","authors":"M. Risser, Steve Pierson","doi":"10.1080/09332480.2023.2179274","DOIUrl":"https://doi.org/10.1080/09332480.2023.2179274","url":null,"abstract":"Abstract This article describes the work of the American Statistical Association (ASA) Advisory Committee on Climate Change Policy (ACCP) which was established in 2008. The committee’s earliest activities included meetings with Congressional committee staffers to hear firsthand their views on climate change, how or whether it should be addressed, and how the statistical perspective may be helpful. Building on the successes in raising awareness on Capitol Hill and beyond regarding the reality of climate change, the group is now pivoting to an emphasis on promoting solutions to climate change. These new efforts will ultimately enable statisticians and data scientists to engage more deeply in the research that is critical to society proactively and successfully addressing the intensifying impacts of climate change.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"19 1","pages":"31 - 34"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85661464","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 : 2023-01-02DOI: 10.1080/09332480.2023.2179258
K. Ensor, D. LaLonde
Abstract The vision of the ASA is to empower a world that relies on data and statistical thinking to drive discovery and inform decisions. The ASA Leadership Institute and the IDEA Forum are strategic initiatives to help the association realize this vision. The IDEA Forum focuses our attention on important global problems and builds strategic partnerships with leaders from all sectors to drive innovation and highlight the critical role played by statisticians in finding solutions to these global problems. This article provides the background on the development of the inaugural IDEA Forum and describes the event.
{"title":"The Influencing Discovery Exploration & Action Forum: An Initiative of the American Statistical Association","authors":"K. Ensor, D. LaLonde","doi":"10.1080/09332480.2023.2179258","DOIUrl":"https://doi.org/10.1080/09332480.2023.2179258","url":null,"abstract":"Abstract The vision of the ASA is to empower a world that relies on data and statistical thinking to drive discovery and inform decisions. The ASA Leadership Institute and the IDEA Forum are strategic initiatives to help the association realize this vision. The IDEA Forum focuses our attention on important global problems and builds strategic partnerships with leaders from all sectors to drive innovation and highlight the critical role played by statisticians in finding solutions to these global problems. This article provides the background on the development of the inaugural IDEA Forum and describes the event.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"38 1","pages":"4 - 8"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82761851","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 : 2023-01-02DOI: 10.1080/09332480.2023.2179273
Bo Li, D. Simpson
Abstract The past two decades have witnessed a great change in the statistics community, as we have become more inclusive and appreciative of different types and areas of research. Interdisciplinary research, including statistical climatology, has developed rapidly in such a background. The Institute for Mathematical and Statistical Innovation (IMSI), funded by the National Science Foundation, is managed by the University of Chicago, Northwestern University, the University of Illinois Chicago, and the University of Illinois Urbana-Champaign, and is hosted at the University of Chicago. IMSI launched in fall 2020 with a mission “to apply rigorous mathematics and statistics to urgent scientific and societal problems, and to spur transformational change in the mathematical sciences.” This article describes the work of IMSI and gives our perspective on the future of the field of statistical climatology.
{"title":"Reflections on the IDEA Forum—Statistics, Climate Change, and Sustainability","authors":"Bo Li, D. Simpson","doi":"10.1080/09332480.2023.2179273","DOIUrl":"https://doi.org/10.1080/09332480.2023.2179273","url":null,"abstract":"Abstract The past two decades have witnessed a great change in the statistics community, as we have become more inclusive and appreciative of different types and areas of research. Interdisciplinary research, including statistical climatology, has developed rapidly in such a background. The Institute for Mathematical and Statistical Innovation (IMSI), funded by the National Science Foundation, is managed by the University of Chicago, Northwestern University, the University of Illinois Chicago, and the University of Illinois Urbana-Champaign, and is hosted at the University of Chicago. IMSI launched in fall 2020 with a mission “to apply rigorous mathematics and statistics to urgent scientific and societal problems, and to spur transformational change in the mathematical sciences.” This article describes the work of IMSI and gives our perspective on the future of the field of statistical climatology.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"11 4 1","pages":"25 - 30"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86654220","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 : 2022-12-08DOI: 10.1080/09332480.2023.2203643
R. Lund, Xueheng Shi
Changepoints are discontinuity times (abrupt changes) in a time-ordered sequence of data. In climate settings, change-points often occur when measuring stations are relocated or gauges are changed. Changepoint methods have multiple uses in climatology, including stationary checks and record homogenization. Statisticians are needed to help resolve the many open problems in the area by developing methods and analyzing data.
{"title":"Changepoint Methods in Climatology","authors":"R. Lund, Xueheng Shi","doi":"10.1080/09332480.2023.2203643","DOIUrl":"https://doi.org/10.1080/09332480.2023.2203643","url":null,"abstract":"Changepoints are discontinuity times (abrupt changes) in a time-ordered sequence of data. In climate settings, change-points often occur when measuring stations are relocated or gauges are changed. Changepoint methods have multiple uses in climatology, including stationary checks and record homogenization. Statisticians are needed to help resolve the many open problems in the area by developing methods and analyzing data.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"35 4 1","pages":"4 - 8"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75771249","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 : 2022-11-23DOI: 10.48550/arXiv.2211.13183
Junbo Wu, Nathaniel Comfort
Public health is the most recent of the biomedical sciences to embrace “precision.” Advocates for “precision public health” (PPH) call for a data-driven, computa¬tional approach to public health, leveraging genomic and other data to inform public health decision-making. Yet, like precision medicine, PPH risks overselling the value of genomic data to deter¬mine health outcomes, but on a population level. History has shown that over-emphasizing heredity tends to disproportion¬ately harm underserved minorities and disadvantaged communities. Comparing and contrasting cur¬rent PPH with an earlier attempt at using genetics to inform pub¬lic health during the Progressive era (1890–1920) highlights some potential risks of genotype-driven preventive public health.
{"title":"Precision Medicine for the Population—The Hope and Hype of Public Health Genomics","authors":"Junbo Wu, Nathaniel Comfort","doi":"10.48550/arXiv.2211.13183","DOIUrl":"https://doi.org/10.48550/arXiv.2211.13183","url":null,"abstract":"Public health is the most recent of the biomedical sciences to embrace “precision.” Advocates for “precision public health” (PPH) call for a data-driven, computa¬tional approach to public health, leveraging genomic and other data to inform public health decision-making. Yet, like precision medicine, PPH risks overselling the value of genomic data to deter¬mine health outcomes, but on a population level. History has shown that over-emphasizing heredity tends to disproportion¬ately harm underserved minorities and disadvantaged communities. Comparing and contrasting cur¬rent PPH with an earlier attempt at using genetics to inform pub¬lic health during the Progressive era (1890–1920) highlights some potential risks of genotype-driven preventive public health.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"6 1","pages":"25 - 27"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78456993","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":"Bayes Rules!","authors":"C. Robert","doi":"10.1080/09332480.2022.2145140","DOIUrl":"https://doi.org/10.1080/09332480.2022.2145140","url":null,"abstract":"This article contains book reviews of Bayes Rules! by Alicia Johnson, Miles Ott, and Mine Dogucu, and Amy’s Luck by David Hand.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"28 1","pages":"50 - 51"},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74434356","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 : 2022-10-02DOI: 10.1080/09332480.2022.2145126
M. Orkin
“Quantum entanglement” is a well-known phenomenon in quantum physics that refers to the ability of widely separated, subatomic objects to be mysteriously connected by sharing a common condition or state. Albert Einstein famously called quantum entanglement “spooky action at a distance.” In “Quantum Entanglement” (The MIT Press Essential Knowledge series, Penguin Random House, 2020), author Jed Brody says, “Two particles are entangled if the measurement of one of them, for all practical purposes, instantly affects the other particle over any distance.” We will discuss a connection between random events that, although not on the quantum level, resemble quantum entanglement in some ways. We metaphorically call this connection “random entanglement.”
{"title":"Random Entanglement","authors":"M. Orkin","doi":"10.1080/09332480.2022.2145126","DOIUrl":"https://doi.org/10.1080/09332480.2022.2145126","url":null,"abstract":"“Quantum entanglement” is a well-known phenomenon in quantum physics that refers to the ability of widely separated, subatomic objects to be mysteriously connected by sharing a common condition or state. Albert Einstein famously called quantum entanglement “spooky action at a distance.” In “Quantum Entanglement” (The MIT Press Essential Knowledge series, Penguin Random House, 2020), author Jed Brody says, “Two particles are entangled if the measurement of one of them, for all practical purposes, instantly affects the other particle over any distance.” We will discuss a connection between random events that, although not on the quantum level, resemble quantum entanglement in some ways. We metaphorically call this connection “random entanglement.”","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"101 1","pages":"15 - 17"},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87978097","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 : 2022-10-02DOI: 10.1080/09332480.2022.2145134
M. Gray
Should different people be treated equally or should, as insurers tell us, different people be treated differently? Is discrimination bad, or is it good? Does today’s reliance on machine-generated algorithms to turn risk into measurable uncertainty differ in essence from trusting the actuarial tables generated by de Moivre from a London coffee house? Do legal regulations assure fair balance of the costs and benefits? What about inclusive social insurance?
{"title":"Risk","authors":"M. Gray","doi":"10.1080/09332480.2022.2145134","DOIUrl":"https://doi.org/10.1080/09332480.2022.2145134","url":null,"abstract":"Should different people be treated equally or should, as insurers tell us, different people be treated differently? Is discrimination bad, or is it good? Does today’s reliance on machine-generated algorithms to turn risk into measurable uncertainty differ in essence from trusting the actuarial tables generated by de Moivre from a London coffee house? Do legal regulations assure fair balance of the costs and benefits? What about inclusive social insurance?","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"27 1","pages":"36 - 39"},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74790219","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 : 2022-10-02DOI: 10.1080/09332480.2022.2145146
F. Liu
This article is a Q&A on differential privacy (DP), a state-of-the-art and popular privacy concept. There are 11 questions, including “What is DP?”, the reasons for its popularity among privacy researchers, examples of real-world applications of DP, and open-source code and platforms on DP. For those who have heard about DP, but have not yet had a chance to read papers and publications on DP (either technical or non-technical) I hope this Q&A will provide something useful and insightful.
{"title":"A Q&A about Differential Privacy","authors":"F. Liu","doi":"10.1080/09332480.2022.2145146","DOIUrl":"https://doi.org/10.1080/09332480.2022.2145146","url":null,"abstract":"This article is a Q&A on differential privacy (DP), a state-of-the-art and popular privacy concept. There are 11 questions, including “What is DP?”, the reasons for its popularity among privacy researchers, examples of real-world applications of DP, and open-source code and platforms on DP. For those who have heard about DP, but have not yet had a chance to read papers and publications on DP (either technical or non-technical) I hope this Q&A will provide something useful and insightful.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"25 1","pages":"52 - 56"},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75568501","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 : 2022-10-02DOI: 10.1080/09332480.2022.2145133
S. Mitra
Data and the analyses thereof are more important than ever for driving critical decision-making in different business applications today. Hence, statistics forms an integral part of most business curriculum across colleges and universities at both undergraduate and graduate levels. This article explores the different facets of teaching statistics (and data science, by extension) to non-STEM majors at a minority-serving institution located in the western United States. It starts with a brief overview of their business statistics course curriculum along with assessment outcomes reported in recent years. It then presents some of my own research in understanding factors that impact student performance and success in this course for potential early detection of “at-risk” students, the role of academic support services like Supplemental Instruction (or SI) in potentially improving student outcomes, the differences in student outcomes between traditional face-to-face and online sections of the course, and lastly the challenges faced during the virtual instruction period precipitated by the COVID-19 pandemic since March 2020. The article concludes with some of my own reflections from teaching this course for over 10 years and the future opportunities to further improve student outcomes in this course, particularly for underserved students.
{"title":"Teaching Statistics and Data Science to Business Students","authors":"S. Mitra","doi":"10.1080/09332480.2022.2145133","DOIUrl":"https://doi.org/10.1080/09332480.2022.2145133","url":null,"abstract":"Data and the analyses thereof are more important than ever for driving critical decision-making in different business applications today. Hence, statistics forms an integral part of most business curriculum across colleges and universities at both undergraduate and graduate levels. This article explores the different facets of teaching statistics (and data science, by extension) to non-STEM majors at a minority-serving institution located in the western United States. It starts with a brief overview of their business statistics course curriculum along with assessment outcomes reported in recent years. It then presents some of my own research in understanding factors that impact student performance and success in this course for potential early detection of “at-risk” students, the role of academic support services like Supplemental Instruction (or SI) in potentially improving student outcomes, the differences in student outcomes between traditional face-to-face and online sections of the course, and lastly the challenges faced during the virtual instruction period precipitated by the COVID-19 pandemic since March 2020. The article concludes with some of my own reflections from teaching this course for over 10 years and the future opportunities to further improve student outcomes in this course, particularly for underserved students.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"20 1","pages":"27 - 35"},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77323342","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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