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Maeda, Hotaka; Zhang, Bo – International Journal of Testing, 2017
The omega (?) statistic is reputed to be one of the best indices for detecting answer copying on multiple choice tests, but its performance relies on the accurate estimation of copier ability, which is challenging because responses from the copiers may have been contaminated. We propose an algorithm that aims to identify and delete the suspected…
Descriptors: Cheating, Test Items, Mathematics, Statistics
Tran, Dung; Lee, Hollylynne; Doerr, Helen – Mathematics Education Research Group of Australasia, 2016
The research reported here uses a pre/post-test model and stimulated recall interviews to assess teachers' statistical reasoning about comparing distributions, when enrolled in a graduate-level statistics education course. We discuss key aspects of the course design aimed at improving teachers' learning and teaching of statistics, and the…
Descriptors: Faculty Development, Thinking Skills, Graduate Students, Statistics
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Neidigh, Robert O.; Dunkelberger, Jake – Journal of Instructional Pedagogies, 2012
In an introductory business statistics course, student groups used sample data to compare a set of sample means to the theoretical sampling distribution. Each group was given a production measurement with a population mean and standard deviation. The groups were also provided an excel spreadsheet with 40 sample measurements per week for 52 weeks…
Descriptors: Group Activities, Student Projects, Sampling, Statistical Distributions
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Watson, Jane; Chance, Beth – Australian Senior Mathematics Journal, 2012
Formal inference, which makes theoretical assumptions about distributions and applies hypothesis testing procedures with null and alternative hypotheses, is notoriously difficult for tertiary students to master. The debate about whether this content should appear in Years 11 and 12 of the "Australian Curriculum: Mathematics" has gone on…
Descriptors: Foreign Countries, Research Methodology, Sampling, Statistical Inference
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Buchanan, Taylor L.; Lohse, Keith R. – Measurement in Physical Education and Exercise Science, 2016
We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…
Descriptors: Researchers, Attitudes, Statistical Significance, Bias
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Broughman, Stephen P.; Swaim, Nancy L.; Hryczaniuk, Cassie A. – National Center for Education Statistics, 2011
In 1988, the National Center for Education Statistics (NCES) introduced a proposal to develop a private school data collection that would improve on the sporadic collection of private school data dating back to 1890 and improve on commercially available private school sampling frames. Since 1989, the U.S. Bureau of the Census has conducted the…
Descriptors: Private Schools, Statistical Significance, Sampling, Statistics
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Vaughn, Brandon K. – Journal of Educational Technology, 2009
In this paper, an interactive teaching approach to introduce the concept of sampling distributions using the statistical software program, R, is shown. One advantage of this approach is that the program R is freely available via the internet. Instructors can easily demonstrate concepts in class, outfit entire computer labs, and/or assign the…
Descriptors: Sampling, Statistics, Computer Software, Statistical Analysis
Pandey, Tej N.; Hubert, Lawrence J. – 1974
This investigation had two major purposes. The first was to explore the use of an inferential technique called Tukey's Jackknife in establishing a confidence interval about cooefficient alpha reliability. The second purpose was to study the robustness of the Feldt and the jackknife procedures when the data fails to satisfy usual normality…
Descriptors: Comparative Analysis, Item Sampling, Statistical Analysis, Statistics
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Kleinke, David J. – Educational and Psychological Measurement, 1972
Descriptors: Analysis of Variance, Comparative Analysis, Norms, Prediction
Cahen, Leonard S.; And Others – 1970
The accuracy of estimating test means for groups of twelfth-grade students by the item-sampling technique was examined. The subjects were from 35 twelfth-grade schools participating in the National Longitudinal Study of Mathematical Abilities. Half of the students in each school were assigned to a treatment condition where they took a complete…
Descriptors: Academic Achievement, Analysis of Variance, Comparative Analysis, Comparative Testing
Helberg, Clay – 1996
Abuses and misuses of statistics are frequent. This digest attempts to warn against these in three broad classes of pitfalls: sources of bias, errors of methodology, and misinterpretation of results. Sources of bias are conditions or circumstances that affect the external validity of statistical results. In order for a researcher to make…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Error of Measurement