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Sullivan, Patrick – Mathematics Teacher: Learning and Teaching PK-12, 2022
Probabilistic reasoning underpins much of middle school students' future work in data analysis and inferential statistics. Unfortunately for many middle school students, probabilistic reasoning is not intuitive. One specific area in which students seem to struggle is determining the probability of compound events (Moritz and Watson 2000). Research…
Descriptors: Mathematics Instruction, Thinking Skills, Middle School Students, Data Analysis
Kazak, Sibel; Pratt, Dave – Research in Mathematics Education, 2021
We examine the challenges of teaching probability through the use of modelling. We argue how an integrated modelling approach might facilitate a coordinated understanding of distribution by marrying theoretical and data-oriented perspectives and present probability as more connected to the social lives of modern-day students. Research is, however,…
Descriptors: Teaching Methods, Mathematics Instruction, Faculty Development, Probability
Kazak, Sibel; Fujita, Taro; Turmo, Manoli Pifarre – Mathematical Thinking and Learning: An International Journal, 2023
In today's age of information, the use of data is very powerful in making informed decisions. Data analytics is a field that is interested in identifying and interpreting trends and patterns within big data to make data-driven decisions. We focus on informal statistical inference and data modeling as a means of developing students' data analytics…
Descriptors: Statistical Inference, Mathematics Skills, Mathematics Instruction, Secondary School Students
Sarafoglou, Alexandra; van der Heijden, Anna; Draws, Tim; Cornelisse, Joran; Wagenmakers, Eric-Jan; Marsman, Maarten – Psychology Learning and Teaching, 2022
Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…
Descriptors: Bayesian Statistics, Thinking Skills, Undergraduate Students, Psychology
Thrasher, Emily; Starling, Tina; Lovett, Jennifer N.; Doerr, Helen M.; Lee, Hollylynne S. – North American Chapter of the International Group for the Psychology of Mathematics Education, 2015
This paper explores the impact on teachers' self-efficacy to teach statistics from a graduate course aimed to develop teachers' knowledge of inferential statistics through engaging in data analysis using technology. This study uses qualitative and quantitative data from the Self-Efficacy to Teach Statistics Survey (Harrell-Williams et al., 2013)…
Descriptors: Mathematics Instruction, Self Efficacy, Graduate Students, Statistical Inference
Petocz, Peter; Sowey, Eric – Teaching Statistics: An International Journal for Teachers, 2012
The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the…
Descriptors: Hypothesis Testing, Statistical Analysis, Foreign Countries, Questioning Techniques

Bankard, Dianne; Fennell, Francis – Arithmetic Teacher, 1991
The focus here is on the students' uses for numbers in both school and home settings. The included activities emphasize a growth and development theme involving various aspects of data collection, data interpretation, probability, and statistics. Also included are parent-child extended activity worksheets. (JJK)
Descriptors: Data Analysis, Data Collection, Elementary Education, Elementary School Mathematics