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Kula, Fulya; Koçer, Rüya Gökhan – Teaching Mathematics and Its Applications, 2020
Difficulties in learning (and thus teaching) statistical inference are well reported in the literature. We argue the problem emanates not only from the way in which statistical inference is taught but also from what exactly is taught as statistical inference. What makes statistical inference difficult to understand is that it contains two logics…
Descriptors: Statistical Inference, Teaching Methods, Difficulty Level, Comprehension
Hancock, Stacey A.; Rummerfield, Wendy – Journal of Statistics Education, 2020
Sampling distributions are fundamental to an understanding of statistical inference, yet research shows that students in introductory statistics courses tend to have multiple misconceptions of this important concept. A common instructional method used to address these misconceptions is computer simulation, often preceded by hands-on simulation…
Descriptors: Teaching Methods, Sampling, Experiential Learning, Computer Simulation
Dinov, Ivo D.; Palanimalai, Selvam; Khare, Ashwini; Christou, Nicolas – Teaching Statistics: An International Journal for Teachers, 2018
Statistical inference involves drawing scientifically-based conclusions describing natural processes or observable phenomena from datasets with intrinsic random variation. We designed, implemented, and validated a new portable randomization-based statistical inference infrastructure (http://socr.umich.edu/HTML5/Resampling_Webapp) that blends…
Descriptors: Statistical Inference, Sampling, Simulation, Computer Oriented Programs
Dogan, C. Deha – Eurasian Journal of Educational Research, 2017
Background: Most of the studies in academic journals use p values to represent statistical significance. However, this is not a good indicator of practical significance. Although confidence intervals provide information about the precision of point estimation, they are, unfortunately, rarely used. The infrequent use of confidence intervals might…
Descriptors: Sampling, Statistical Inference, Periodicals, Intervals
Forbes, Sharleen; Chapman, Jeanette; Harraway, John; Stirling, Doug; Wild, Chris – Statistics Education Research Journal, 2014
For many years, students have been taught to visualise data by drawing graphs. Recently, there has been a growing trend to teach statistics, particularly statistical concepts, using interactive and dynamic visualisation tools. Free down-loadable teaching and simulation software designed specifically for schools, and more general data visualisation…
Descriptors: Foreign Countries, Visualization, Graphs, Statistical Data
Sanches, Cristina; Gouveia-Pereira, Maria; Carugati, Felice – British Journal of Educational Psychology, 2012
Background: The current paper is based on two different approaches. One is the relational model of authority (Tyler & Lind, 1992), which addresses the effects of justice perceptions on the legitimacy of authorities and behavioural compliance. The other is Emler and Reicher's theory (1995, 2005), which explains the involvement of adolescents in…
Descriptors: Evidence, Adolescents, Teaching Methods, Justice
Johnson, H. Dean; Evans, Marc A. – Australian Mathematics Teacher, 2008
Understanding the concept of the sampling distribution of a statistic is essential for the understanding of inferential procedures. Unfortunately, this topic proves to be a stumbling block for students in introductory statistics classes. In efforts to aid students in their understanding of this concept, alternatives to a lecture-based mode of…
Descriptors: Class Activities, Intervals, Computer Software, Sampling
Feng, Mingyu; Beck, Joseph E.; Heffernan, Neil T. – International Working Group on Educational Data Mining, 2009
A basic question of instructional interventions is how effective it is in promoting student learning. This paper presents a study to determine the relative efficacy of different instructional strategies by applying an educational data mining technique, learning decomposition. We use logistic regression to determine how much learning is caused by…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Sampling, Statistical Inference
Marsh, Michael T. – American Journal of Business Education, 2009
Regardless of the related discipline, students in statistics courses invariably have difficulty understanding the connection between the numerical values calculated for end-of-the-chapter exercises and their usefulness in decision making. This disconnect is, in part, due to the lack of time and opportunity to actually design the experiments and…
Descriptors: Online Courses, Statistical Analysis, Sampling, Teaching Methods

Ojeda, Mario Miguel; Sahai, Hardeo – International Journal of Mathematical Education in Science and Technology, 2002
Discusses some key statistical concepts in probabilistic and non-probabilistic sampling to provide an overview for understanding the inference process. Suggests a statistical model constituting the basis of statistical inference and provides a brief review of the finite population descriptive inference and a quota sampling inferential theory.…
Descriptors: Educational Strategies, Higher Education, Mathematics Education, Probability

Saldanha, Luis; Thompson, Patrick – Educational Studies in Mathematics, 2002
Distinguishes two conceptions of sample and sampling that emerged in the context of a teaching experiment conducted in a high school statistics class. Suggests that the conception of a sample as a quasi- proportional, small-scale version of the population is a powerful one to target for instruction. (Author/KHR)
Descriptors: Concept Formation, Mathematics Instruction, Sampling, Secondary Education
Meletiou-Mavrotheris, Maria – International Journal of Computers for Mathematical Learning, 2004
While technology has become an integral part of introductory statistics courses, the programs typically employed are professional packages designed primarily for data analysis rather than for learning. Findings from several studies suggest that use of such software in the introductory statistics classroom may not be very effective in helping…
Descriptors: Educational Technology, Statistics, Statistical Inference, Teaching Methods
Garofalo, Joe; Juersivich, Nicole – NCSSSMST Journal, 2007
There is much research that documents what many teachers know, that students struggle with many concepts in probability and statistics. This article presents two sample activities the authors use to help preservice teachers develop ideas about how they can use technology to promote their students' ability to understand mathematics and connect…
Descriptors: Preservice Teachers, Statistical Inference, Sampling, Probability

Geiger, Vince; Wallace, Robyn – Australian Mathematics Teacher, 1987
Presents teaching activities that are intended to be used to teach statistics to students in a high school mathematics program. Includes a worksheet of eight discussion questions on statistics, four activities on sampling bias, two experiments on sampling techniques, and a game known as "capture-recapture." (TW)
Descriptors: Mathematical Concepts, Mathematics Curriculum, Mathematics Education, Mathematics Instruction
Reading, Chris – Statistics Education Research Journal, 2004
Variation is a key concept in the study of statistics and its understanding is a crucial aspect of most statistically related tasks. This study aimed to extend and apply a hierarchy for describing students' understanding of variation that was developed in a sampling context to the context of a natural event in which variation occurs. Students aged…
Descriptors: Weather, Classification, Secondary School Students, Student Evaluation