An Intuitive Introduction to Hypothesis Testing

Dambolena, Ismael G.; Eriksen, Steven E.; Kopcso, David P.

doi:10.1287/ited.1080.0019

Cited by 3 publications

(3 citation statements)

References 27 publications

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“…The aim of the game was to ground the basic concepts and to experience the notions, the logic, and the method of hypothesis testing by practical activities. Though this method was introduced earlier (Lawton, 2009;Dambolena et al, 2009), our approach places greater emphasis on the hands-on in-class experiment.…”

Section: Our Decisionmentioning

confidence: 99%

Interdisciplinary Secondary-School Workshop

Péter

Borovcnik

2020

Teach. Math. Comput. Sci.

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The paper describes a teaching unit of four hours with talented students aged 15-18. The workshop was designed as a problem-based sequence of tasks and was intended to deal with judging dice whether they are regular or loaded. We first introduced the students to the physics of free rotations of rigid bodies to develop the physics background of rolling dice. The highlight of this part was to recognise that cubes made from homogeneous material are the optimal form for six-sided objects leading to equal probabilities of the single faces. Experiments with all five regular bodies would lead to similar results; nevertheless, in our experiments we focused on regular cubes. This reinsures that the participants have their own experience with the context. Then, we studied rolling dice from the probabilistic point of view and-step-by-step-by extending tasks and simulations, we introduced the idea of the chi-squared test interactively with the students. The physics and the statistics part of the paper are largely independent and can be also be read separately. The success of the statistics part is best described by the fact that the students recognised that in some cases of loaded dice, it is easier to detect that property and in other cases one would need many data to make a decision with small error probabilities. A physical examination of the dice under inspection can lead to a quick and correct decision. Yet, such a physical check may fail for some reason. However, a statistical test will always lead to reasonable decision, but may require a large database. Furthermore, especially for smaller datasets, balancing the risk of different types of errors remains a key issue, which is a characteristic feature of statistical testing.

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Section: Our Decisionmentioning

confidence: 99%

Interdisciplinary Secondary-School Workshop

Péter

Borovcnik

2020

Teach. Math. Comput. Sci.

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“…Hence, it is important for those young students, in their early stage of learning inferential statistics, to grasp the idea of hypothesis testing in order that they can comfortably apply various hypothesis testing methods later. To promote effective teaching of hypothesis testing to young students, statistics educators have proposed many innovative approaches to presenting in classroom environment the logic and concepts involved in hypothesis testing, for example, Dambolena et al (), Holland (), and Nordmoe ().…”

Section: Introductionmentioning

confidence: 99%

Do you catch undersized fish? Let's Go fishing to learn some important concepts in multiple testing

Zheng

2016

Teaching Statistics

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In the era of Big Data, because of diminishing cost of data collection and storage, a large number of statistical tests may even possibly be conducted all together by a high school student to seek for some 'exciting' new scientific findings. In this article, we propose an interesting approach to introduce students to some important concepts in multiple testing by an analogous example of net fishing. The proposed teaching approach is fun and requires no mathematical calculation.

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“…Numerous studies document misconceptions about averages (e.g., Watson 2007); chance events (e.g., Albert 2003, Garfield 2002, Hirsch and O'Donnell 2001; measures of variability (e.g., Ben-Zvi andGarfield 2004, Watson andKelly 2007); sampling distributions (e.g., Chance et al 2004); confidence intervals (e.g., Grant and Nathan 2008); and hypothesis testing (e.g., Dambolena et al 2009, Haller and Krauss 2002, Vallecillos 2002. Additional references going back to the late 1970s are provided in delMas et al (2007) and, for engineering disciplines, in Evans et al (2003).…”

Section: Introductionmentioning

confidence: 99%

Identifying Addressable Impediments to Student Learning in an Introductory Statistics Course

Stevens

Palocsay

2012

INFORMS Transactions on Education

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palocssw@jmu.edu} U sing performance data on a common test instrument administered to more than 4,000 business statistics students studying under 16 different instructors over a period of 6.5 years, we identify areas of consistent student weakness. In addition to verifying difficulties found by earlier researchers, we document a fundamental problem in students' ability to reason with cumulative probabilities, a problem with implications for solving problems with both discrete and continuous distributions. Our performance data also suggest that it may be useful to view statistics problems using a taxonomy based more on solution procedure than on traditional statistics topics. We employ a new methodology based on cluster analysis to identify areas where the observed student difficulties may be particularly addressable. Finally, we offer some preliminary findings on how these problems may be addressed with practical teaching suggestions based on the approaches employed by our more successful instructors.

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An Intuitive Introduction to Hypothesis Testing

Cited by 3 publications

References 27 publications

Interdisciplinary Secondary-School Workshop

Interdisciplinary Secondary-School Workshop

Do you catch undersized fish? Let's Go fishing to learn some important concepts in multiple testing

Identifying Addressable Impediments to Student Learning in an Introductory Statistics Course

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