Surveying the Landscape of Numbers in U.S. News

The news arguably serves to inform the quantitative reasoning (QR) of news audiences. Before one can contemplate how well the news serves this function, we first need to determine how much QR typical news stories require from readers. This paper assesses the amount of quantitative content present in a wide array of media sources, and the types of QR required for audiences to make sense of the information presented. We build a corpus of 230 US news reports across four topic areas (health, science, economy, and politics) in February 2020. After classifying reports for QR required at both the conceptual and phrase levels, we find that the news stories in our sample can largely be classified along a single dimension: The amount of quantitative information they contain. There were two main types of quantitative clauses: those reporting on magnitude and those reporting on comparisons. While economy and health reporting required significantly more QR than science or politics reporting, we could not reliably differentiate the topic area based on story-level requirements for quantitative knowledge and clause-level quantitative content. Instead, we find three reliable clusters of stories based on the amounts and types of quantitative information in the news stories.

Considering What Counts: Claims about Nearly-Ubiquitous Social Problems

Press coverage of a recent survey suggests that sexual harassment is nearly ubiquitous in the UK. Thinking critically about claims of nearly-ubiquitous social problems requires: (1) asking how the statistic was produced; (2) considering questions of measurement; and (3) recognizing that the the most severe forms that social problems take tend to be much less common than less serious forms

Guns and the Limits of Numeracy: Review of How America Got Its Guns: A History of the Gun Violence Crisis, by William Briggs.

William Briggs. 2017. How America Got Its Guns: A History of the Gun Violence Crisis; (Albuquerque, University of New Mexico Press). Paperback: ISBN 978-0-8263-5813-4. E-book ISBN 978-0-8263-5814-1. Mathematician William Briggs (co-author of the well-regarded Understanding and Using Mathematics) has written a remarkably thorough and evenhanded analysis of gun policy in the United States that draws upon the work of historians, legal scholars, social scientists, and advocates. He gives respectful hearings to claims about the importance of both gun rights and gun control. The breadth of his coverage makes it almost certain that any reader will discover new angles for thinking about gun issues.

The Cost of Mathematical Illiteracy: Review of Innumeracy in the Wild by Ellen Peters (2020)

In Innumeracy in the Wild (Oxford University Press, 2020), Ellen Peters, a researcher in decision science, persuasively argues that numeracy skills, numeric confidence, and our intuitive sense for numbers impact our lifelong outcomes in health and wellbeing. Peters draws from research and real-world examples to show how daily life for innumerate people is different from that of numerate people and makes practical recommendations on improving how we communicate numerical information.

Quantitative Literacy and Guns

Briggs, William. 2017. How America Got Its Guns: A History of the Gun Violence Crisis; (Albuquerque, University of New Mexico Press). 352 pp. Paperback: ISBN 978-0-8263-5813-4. E-book ISBN 978-0-8263-5814-1. Quantitative literacy and statistics are just two of many disciplines required to understand the problem of gun violence in America. However, it’s also useful to appreciate their limitations in an issue that is so complex.

Be Careful! That is Probably Bullshit! Review of Calling Bullshit: The Art of Skepticism in a Data-Driven World by Carl T. Bergstrom and Jevin D. West

Bergstrom, C. T., & West, J. D. 2021. Calling Bullshit: The Art of Skepticism in a Data-Driven World. NY: Random House. 336 pp. ISBN 978-0525509189 The authors provide a journey through the numerical bullshit that surrounds our daily lives. Each chapter has multiple examples of specific types of bullshit that each of us experience on any given day. Most importantly, information on how to identify bullshit and refute it are provided so that reader finishes the book with a set of skills to be a more engaged and critical interpreter of information. The writing has a quick and lively pace that a wide audience will enjoy.

Lessons from the Pandemic

The COVID-19 pandemic highlights the importance of quantitative literacy--for policy makers and the public at large. While all aspects of numeracy have been shown relevant to the past year, our need for broader statistical literacy appear particularly pressing. Pandemic experiences may motivate greater interest in developing numeracy skills.

Confidence Intervals of COVID-19 Vaccine Efficacy Rates

This tutorial uses publicly available data from drug makers and the Food and Drug Administration to guide learners to estimate the confidence intervals of COVID-19 vaccine efficacy rates with a Bayesian framework. Under the classical approach, there is no probability associated with a parameter, and the meaning of confidence intervals can be misconstrued by inexperienced students. With Bayesian statistics, one can find the posterior probability distribution of an unknown parameter, and state the probability of vaccine efficacy rate, which makes the communication of uncertainty more flexible. We use a hypothetical example and a real baseball example to guide readers to learn the beta-binomial model before analyzing the clinical trial data. This note is designed to be accessible for lower-level college students with elementary statistics and elementary algebra skills.

Investigating Alignment in a Quantitative Literacy Course for Social Sciences Students

The Numeracy Centre at the University of Cape Town has taught a one-semester quantitative literacy course for social sciences students since 1999. This study aims to provide an example for how the design of such a course can be assessed for alignment with quantitative reasoning goals. We propose a framework of learning outcomes for the course and use that framework to analyse the assessments and student performance on them. We find that just under half of the overall mark for the course was devoted to the interpretation and communication of quantitative information (our “main” outcomes), and about a quarter was devoted to the performing of calculations. The analysis revealed that statistics outcomes were under-represented in the make-up of the overall course mark, and assessment of these outcomes was restricted almost entirely to the two final examinations. The results of the analysis of the alignment between outcomes and assessment are useful to inform discussions about changes to the course curriculum. The analysis of student performance on the different outcomes provides insights which are useful for informing improvements to our teaching approach. The analysis demonstrates a relatively straightforward procedure that can be used or adapted by researchers in other institutions for ongoing monitoring of alignment between course outcomes, teaching, and assessment.

Engaging Social Science Students with Statistics: Opportunities, Challenges and Barriers

In 2012, in a bid to improve the quantitative methods training of social science students in the UK, the £19.5 million Q-Step project was launched. This investment demonstrated a significant commitment to changing how we train social science students in quantitative research methods in the UK. The project has involved eighteen higher education institutions exploring and trialling potential ways of engaging social science students with quantitative approaches. This paper reflects on the activities of one Q-Step centre based in the School of Social Sciences at Cardiff University. As well as describing some of the pedagogic changes that have been implemented, the paper draws on data to begin to evaluate the success of new approaches. Specifically, data showing the proportion of students undertaking a quantitative final-year dissertation project is used to measure the impact of these activities. The data presented in this paper suggest that resistance to learning quantitative research methods and engaging with such techniques has decreased. The data also indicates that students see this learning as beneficial for their own employability. Despite this, closer analysis reveals that several students change their mind about employing quantitative methods in their own research part way through their dissertation journey. We argue that while social science students are comfortable learning about quantitative approaches, they are less confident at applying these techniques. Thus, the paper argues that there is a wider challenge of demonstrating the relevance and appropriateness of such approaches to understanding the social world.