It has been widely documented that many undergraduate students demonstrate antipathy towards statistics. This paper documents the findings from an investigation of statistics education in a sport and exercise science department at The University of Chichester in the UK. Sports science is a multidisciplinary subject that encompasses biomechanics, physiology, and psychology. The university had a suite of four programmes each with a different emphasis in terms of subject discipline. Academics’ use and interpretation of statistics are influenced by their subject specialism within sports science. The investigation evaluated the differences in examination performance between degree programmes, gender and previous mathematics achievement. Findings from the analysis of examination results found mathematics qualification to significantly affect achievement in statistics examinations. Qualitative analysis provided contextual detail that support the need for professional and pedagogic development.
{"title":"Reaching out to the sports science setting: the impact of academic practice on students’ statistical literacy","authors":"Beverley J Hale","doi":"10.52041/srap.11501","DOIUrl":"https://doi.org/10.52041/srap.11501","url":null,"abstract":"It has been widely documented that many undergraduate students demonstrate antipathy towards statistics. This paper documents the findings from an investigation of statistics education in a sport and exercise science department at The University of Chichester in the UK. Sports science is a multidisciplinary subject that encompasses biomechanics, physiology, and psychology. The university had a suite of four programmes each with a different emphasis in terms of subject discipline. Academics’ use and interpretation of statistics are influenced by their subject specialism within sports science. The investigation evaluated the differences in examination performance between degree programmes, gender and previous mathematics achievement. Findings from the analysis of examination results found mathematics qualification to significantly affect achievement in statistics examinations. Qualitative analysis provided contextual detail that support the need for professional and pedagogic development.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128459825","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}
The goal of teaching statistics is to foster an adult population capable of reasoning from and about data and making informed decisions based on quantitative information in the workplace, in their personal lives and as citizens. This paper describes examples of data available to those involved in the design and delivery of education and some of the statistical skills and reasoning necessary to understand, interpret and use that information about schools, teachers, and students to improve their educational systems. Educators in the United States increasingly have access to data such as achievement trends over time, item analyses from high stakes tests, or comparison data for states and comparable systems that can help them develop ways to improve student learning. Unfortunately, few educators have sufficient understanding of statistics to make use of this data to help prevent errors in decision-making.
{"title":"The role of statistics in improving education","authors":"Gail Burrill","doi":"10.52041/srap.11101","DOIUrl":"https://doi.org/10.52041/srap.11101","url":null,"abstract":"The goal of teaching statistics is to foster an adult population capable of reasoning from and about data and making informed decisions based on quantitative information in the workplace, in their personal lives and as citizens. This paper describes examples of data available to those involved in the design and delivery of education and some of the statistical skills and reasoning necessary to understand, interpret and use that information about schools, teachers, and students to improve their educational systems. Educators in the United States increasingly have access to data such as achievement trends over time, item analyses from high stakes tests, or comparison data for states and comparable systems that can help them develop ways to improve student learning. Unfortunately, few educators have sufficient understanding of statistics to make use of this data to help prevent errors in decision-making.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"414 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114098607","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}
Meta-analysis is the quantitative integration of empirical studies that address the same or similar issues. It is usually the best way to draw research-based conclusions that can guide evidence-based practice by professionals, and evidence-based decision making by public policy makers. Meta-analysis is so important that students should learn about it very early in their statistics education. The close links between meta-analysis and practical conclusions drawn from bodies of research mean that meta-analysis is a vital element in outreach from statistics education. I describe software that uses forest plots to make the basic ideas of meta-analysis accessible, and my experience using it with beginning students. I use the software to illustrate two major models for meta-analysis, and introduce graphical extensions to forest plots that illustrate how the crucial topic of moderator analysis can be explained and, in simple cases, interpreted visually.
{"title":"Using forest plots to introduce meta-analysis, including simple moderator analysis, early in statistics education","authors":"G. Cumming","doi":"10.52041/srap.11504","DOIUrl":"https://doi.org/10.52041/srap.11504","url":null,"abstract":"Meta-analysis is the quantitative integration of empirical studies that address the same or similar issues. It is usually the best way to draw research-based conclusions that can guide evidence-based practice by professionals, and evidence-based decision making by public policy makers. Meta-analysis is so important that students should learn about it very early in their statistics education. The close links between meta-analysis and practical conclusions drawn from bodies of research mean that meta-analysis is a vital element in outreach from statistics education. I describe software that uses forest plots to make the basic ideas of meta-analysis accessible, and my experience using it with beginning students. I use the software to illustrate two major models for meta-analysis, and introduce graphical extensions to forest plots that illustrate how the crucial topic of moderator analysis can be explained and, in simple cases, interpreted visually.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129756928","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}
Comparing two data sets can be a powerful tool in light of its use toward a consideration of inferential statistics. Both informal and formal statistical reasoning are developed when comparing data sets, which has implications for researchers who investigate ways to help students transfer from informal to formal reasoning. In this paper, we examined students’ reasoning to identify how they treat data value, center, spread, and sample, which are important factors in inferential statistics. Students' understanding of data value, center, and spread were appropriate, but that of sample was not. From the results, we suggest instructional ideas for a task which can connect descriptive and inferential statistics.
{"title":"Comparison of data sets as a precursor to inferential statistics","authors":"Minsun Park, Mimi Park, Eun-Sung Ko, K. Lee","doi":"10.52041/srap.11106","DOIUrl":"https://doi.org/10.52041/srap.11106","url":null,"abstract":"Comparing two data sets can be a powerful tool in light of its use toward a consideration of inferential statistics. Both informal and formal statistical reasoning are developed when comparing data sets, which has implications for researchers who investigate ways to help students transfer from informal to formal reasoning. In this paper, we examined students’ reasoning to identify how they treat data value, center, spread, and sample, which are important factors in inferential statistics. Students' understanding of data value, center, and spread were appropriate, but that of sample was not. From the results, we suggest instructional ideas for a task which can connect descriptive and inferential statistics.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131029758","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}
Statistics have great potential to generate knowledge and serve as basis for decisions taken by policy makers and the public; however, the understanding of the facts and figures behind policies and political processes is confronted with growing difficulties. This is because many people do not know about statistics or do not care about them as they do not understand them. This paper explored innovative tools for exploring statistics and ways of disseminating them in such a way that it would be understood by the common man. The main focus of the paper is on methods to enhance the understanding and presentation of statistical data. This would be done to increase transparency regarding the National Statistical Systems, to foster the ability of critical data interpretation through the public, to prevent misuse of data, and to improve confidence in policies based on statistical data.
{"title":"Making statistics friendly to users.","authors":"C. Nwosu","doi":"10.52041/srap.11404","DOIUrl":"https://doi.org/10.52041/srap.11404","url":null,"abstract":"Statistics have great potential to generate knowledge and serve as basis for decisions taken by policy makers and the public; however, the understanding of the facts and figures behind policies and political processes is confronted with growing difficulties. This is because many people do not know about statistics or do not care about them as they do not understand them. This paper explored innovative tools for exploring statistics and ways of disseminating them in such a way that it would be understood by the common man. The main focus of the paper is on methods to enhance the understanding and presentation of statistical data. This would be done to increase transparency regarding the National Statistical Systems, to foster the ability of critical data interpretation through the public, to prevent misuse of data, and to improve confidence in policies based on statistical data.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121488039","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}
This paper presents on how I conducted the statistical literacy program among barangay (village) officials and how these officials applied what they have learned in their respective barangays. Moreover, I portrayed in this paper how I provided an intensive program for an introductory statistics course which is called “Senior High School Students Literacy Program” with an objective of providing initial knowledge in Statistics to the participants, win statistics quiz contest as well as encouraging them to pursue a degree in Statistics. The programs for both barangay officials and senior high school students gained positive results as manifested on: 1). how the barangay officials collected, presented and analyzed data on their respective barangays 2). how the senior students won statistics quiz contest conducted by the NSO of the Philippines and the PSA and 3). the number of students who pursued BS Statistics degree.
{"title":"Statistical literacy among barangay officials and senior high school students: a university outreach program","authors":"C. Refugio","doi":"10.52041/srap.11605","DOIUrl":"https://doi.org/10.52041/srap.11605","url":null,"abstract":"This paper presents on how I conducted the statistical literacy program among barangay (village) officials and how these officials applied what they have learned in their respective barangays. Moreover, I portrayed in this paper how I provided an intensive program for an introductory statistics course which is called “Senior High School Students Literacy Program” with an objective of providing initial knowledge in Statistics to the participants, win statistics quiz contest as well as encouraging them to pursue a degree in Statistics. The programs for both barangay officials and senior high school students gained positive results as manifested on: 1). how the barangay officials collected, presented and analyzed data on their respective barangays 2). how the senior students won statistics quiz contest conducted by the NSO of the Philippines and the PSA and 3). the number of students who pursued BS Statistics degree.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125261655","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}
Risk is a major factor in health, with a strong focus on minimising risk wherever possible. The mathematical starting point is probability. Reliable or relevant data is often missing or hard to get. Moreover, the results of studies are all too easily interpreted wrongly – even by medical experts. Usually it is seen as useful to have more information in making decisions. As we show below this is not always true; we will use the exemplar of breast cancer and screening as an illustration throughout this paper to explain circumstances where there is ‘more information and more uncertainty’ following Knight and type 2 errors. We identify the different stakeholders and parts of their internal criteria that form their ‘rationality’, which may well be idiosyncratic. The intention is to pave the way for a ‘shared’ decision which is best for individuals and for society simultaneously. Statistics educators will find an important field of research and teaching.
{"title":"Risk in health: more information and more uncertainty","authors":"M. Borovcnik, R. Kapadia","doi":"10.52041/srap.11702","DOIUrl":"https://doi.org/10.52041/srap.11702","url":null,"abstract":"Risk is a major factor in health, with a strong focus on minimising risk wherever possible. The mathematical starting point is probability. Reliable or relevant data is often missing or hard to get. Moreover, the results of studies are all too easily interpreted wrongly – even by medical experts. Usually it is seen as useful to have more information in making decisions. As we show below this is not always true; we will use the exemplar of breast cancer and screening as an illustration throughout this paper to explain circumstances where there is ‘more information and more uncertainty’ following Knight and type 2 errors. We identify the different stakeholders and parts of their internal criteria that form their ‘rationality’, which may well be idiosyncratic. The intention is to pave the way for a ‘shared’ decision which is best for individuals and for society simultaneously. Statistics educators will find an important field of research and teaching.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125528161","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}
It is well recognised that hands-on school activities can encourage engagement and learning. However, for many years such activities with a competitive element have taken a back seat to the promotion of activities that encourage cooperation. With careful consideration to the inclusion of all class members at KS3 level, Conker Statistics have worked closely with secondary school teachers in developing two themed sets of activities that have elements of competition and cooperation. The Nappy Changing Challenge, designed to raise awareness of childcare, uses realistic baby dolls and real nappies. A well designed data collection form provides the necessary guidance to perform the three stages of the activity including estimation, opinions and measurement. Analysis of the data collected motivates class discussion and presentation of the key results. Classroom Olympics, launched at the English Institute of Sports in 2010, encourages all pupils, regardless of their athletic ability, to take part in competitive activities such as the bean bag shot put and standing start triple jump. To date over 2000 students have taken part in these activities within the classroom and at school events.We discuss out experience of The Nappy Challenge and Classroom Olympics.
{"title":"Nappy changing challenge and classroom olympics: competitive and cooperative hands on data collection activities","authors":"B. Payne","doi":"10.52041/srap.11107","DOIUrl":"https://doi.org/10.52041/srap.11107","url":null,"abstract":"It is well recognised that hands-on school activities can encourage engagement and learning. However, for many years such activities with a competitive element have taken a back seat to the promotion of activities that encourage cooperation. With careful consideration to the inclusion of all class members at KS3 level, Conker Statistics have worked closely with secondary school teachers in developing two themed sets of activities that have elements of competition and cooperation. The Nappy Changing Challenge, designed to raise awareness of childcare, uses realistic baby dolls and real nappies. A well designed data collection form provides the necessary guidance to perform the three stages of the activity including estimation, opinions and measurement. Analysis of the data collected motivates class discussion and presentation of the key results. Classroom Olympics, launched at the English Institute of Sports in 2010, encourages all pupils, regardless of their athletic ability, to take part in competitive activities such as the bean bag shot put and standing start triple jump. To date over 2000 students have taken part in these activities within the classroom and at school events.We discuss out experience of The Nappy Challenge and Classroom Olympics.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121029284","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}
Official statistical information is a public good and therefore should become common heritage in a full sense. One of the fundamental aims of a National Institute of Statistics is to increase people’s statistical literacy. In order to achieve this, Istat decided to review its communication and didactic priorities and strategies and to start from young people: they must be considered as one of the key groups towards which new statistical 3 literacy activities should be directed. However, the main difference from the past lies in the idea of using the high computer technology and web 2.0 skills which young people nowadays possess in order to attract them to statistics. Our goal is clear: to increase young people’s statistical awareness in order to make them more responsible citizens. Many activities have been already performed and many others are going to be performed.
{"title":"Istat’s new strategies to increase statistical literacy","authors":"B. Ascari, Francesco Michele Mortati","doi":"10.52041/srap.11109","DOIUrl":"https://doi.org/10.52041/srap.11109","url":null,"abstract":"Official statistical information is a public good and therefore should become common heritage in a full sense. One of the fundamental aims of a National Institute of Statistics is to increase people’s statistical literacy. In order to achieve this, Istat decided to review its communication and didactic priorities and strategies and to start from young people: they must be considered as one of the key groups towards which new statistical 3 literacy activities should be directed. However, the main difference from the past lies in the idea of using the high computer technology and web 2.0 skills which young people nowadays possess in order to attract them to statistics. Our goal is clear: to increase young people’s statistical awareness in order to make them more responsible citizens. Many activities have been already performed and many others are going to be performed.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125248491","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}
Stephanie Lem, P. Onghena, L. Verschaffel, W. Dooren
Representational fluency consists of several aspects, like the efficiency with which one uses a particular representation and the efficiency with which one is able to coordinate between different representations. In this study we focused on this last element, more specifically on coordinating between histograms and box plots. Participants were 167 first year university students. They were asked to match box plots and histograms of the same distributions and to explain their matches. We found that students had one major difficulty when interpreting box plots: They tended to interpret the area of box plots incorrectly by assuming that a larger area represented more observations than a smaller area. In both items this led to incorrect matches and to incorrect explanations of these matches. Furthermore, students displayed several other misinterpretations.
{"title":"Coordinating between histograms and box plots","authors":"Stephanie Lem, P. Onghena, L. Verschaffel, W. Dooren","doi":"10.52041/srap.11706","DOIUrl":"https://doi.org/10.52041/srap.11706","url":null,"abstract":"Representational fluency consists of several aspects, like the efficiency with which one uses a particular representation and the efficiency with which one is able to coordinate between different representations. In this study we focused on this last element, more specifically on coordinating between histograms and box plots. Participants were 167 first year university students. They were asked to match box plots and histograms of the same distributions and to explain their matches. We found that students had one major difficulty when interpreting box plots: They tended to interpret the area of box plots incorrectly by assuming that a larger area represented more observations than a smaller area. In both items this led to incorrect matches and to incorrect explanations of these matches. Furthermore, students displayed several other misinterpretations.","PeriodicalId":226423,"journal":{"name":"Statistics Education and Outreach IASE Satellite Conference","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134026603","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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