KEY MESSAGE(S): - Medical research will not improve if we simply interpret our results using the clear-cut difference between statistical significance and non-significance - Medical researchers should be more interested in the size of the observed result than in its statistical significance - Confidence intervals provide more information than P-values.
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Poster presented at the 14th Congress of the European Society for Research in Mathematics Education, Free University of Bozen-Bolsano, Italy.
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Citizens regularly search the Web to make informed decisions on daily life questions, like online purchases, but how they reason with the results is unknown. This reasoning involves engaging with data in ways that require statistical literacy, which is crucial for navigating contemporary data. However, many adults struggle to critically evaluate and interpret such data and make data-informed decisions. Existing literature provides limited insight into how citizens engage with web-sourced information. We investigated: How do adults reason statistically with web-search results to answer daily life questions? In this case study, we observed and interviewed three vocationally educated adults searching for products or mortgages. Unlike data producers, consumers handle pre-existing, often ambiguous data with unclear populations and no single dataset. Participants encountered unstructured (web links) and structured data (prices). We analysed their reasoning and the process of preparing data, which is part of data-ing. Key data-ing actions included judging relevance and trustworthiness of the data and using proxy variables when relevant data were missing (e.g., price for product quality). Participants’ statistical reasoning was mainly informal. For example, they reasoned about association but did not calculate a measure of it, nor assess underlying distributions. This study theoretically contributes to understanding data-ing and why contemporary data may necessitate updating the investigative cycle. As current education focuses mainly on producers’ tasks, we advocate including consumers’ tasks by using authentic contexts (e.g., music, environment, deferred payment) to promote data exploration, informal statistical reasoning, and critical web-search skills—including selecting and filtering information, identifying bias, and evaluating sources.
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This research paper looks at a selection of science-fiction films and its connection with the progression of the use of television, telephone and print media. It also analyzes statistical data obtained from a questionnaire conducted by the research group regarding the use of communication media.
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![Does Science-Fiction predict [or change] the future?](https://publinova-harvester-content-prod.s3.amazonaws.com/thumbnails/files/previews/pdf/20250506145555255024.adbf7edd-9619-4d0e-9a17-e0e7096adc7f-thumbnail-400x300.png)
With summaries in Dutch, Esperanto and English. DOI: 10.4233/uuid:d7132920-346e-47c6-b754-00dc5672b437 "The subject of this study is deformation analysis of the earth's surface (or part of it) and spatial objects on, above or below it. Such analyses are needed in many domains of society. Geodetic deformation analysis uses various types of geodetic measurements to substantiate statements about changes in geometric positions.Professional practice, e.g. in the Netherlands, regularly applies methods for geodetic deformation analysis that have shortcomings, e.g. because the methods apply substandard analysis models or defective testing methods. These shortcomings hamper communication about the results of deformation analyses with the various parties involved. To improve communication solid analysis models and a common language have to be used, which requires standardisation.Operational demands for geodetic deformation analysis are the reason to formulate in this study seven characteristic elements that a solid analysis model needs to possess. Such a model can handle time series of several epochs. It analyses only size and form, not position and orientation of the reference system; and datum points may be under influence of deformation. The geodetic and physical models are combined in one adjustment model. Full use is made of available stochastic information. Statistical testing and computation of minimal detectable deformations is incorporated. Solution methods can handle rank deficient matrices (both model matrix and cofactor matrix). And, finally, a search for the best hypothesis/model is implemented. Because a geodetic deformation analysis model with all seven elements does not exist, this study develops such a model.For effective standardisation geodetic deformation analysis models need: practical key performance indicators; a clear procedure for using the model; and the possibility to graphically visualise the estimated deformations."
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Marketing Analytics provides guidelines in the application of statistics using IBM SPSS Statistics Software (SPSS) for students and professionals using quantitative methods in marketing and consumer behavior. With simple language and a practical, screenshot-led approach, the book presents 11 multivariate techniques and the steps required to perform analysis. Each chapter contains a brief description of the technique, followed by the possible marketing research applications. One of these applications is then used in detail to illustrate its applicability in a research context, including the needed SPSS commands and illustrations. Each chapter also includes practical exercises that require the readers to perform the technique and interpret the results, equipping students with the necessary skills to apply statistics by means of SPSS in marketing and consumer research. Finally, there is a list of articles employing the technique that can be used for further reading.This textbook provides introductory material for advanced undergraduate and postgraduate students studying marketing and consumer analytics, teaching methods along with practical software-applied training using SPSS. Support material includes two real data sets to illustrate the techniques’ applications and PowerPoint slides providing a step-by-step guide to the analysis and commented outcomes. Professionals are invited to use the book to select and use the appropriate analytics for their specific context.
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KEY MESSAGE: • Statistical significance testing alone is not the most adequate manner to evaluate if there is indeed a clinically relevant effect • Effect sizes should be added to significance testing • Effect sizes facilitate the decision whether a clinically relevant effect is found, helps determining the sample size for future studies, and facilitates comparison between scientific studies
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