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Showing 1 to 15 of 17 results Save | Export
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Migliavaca, Celina Borges; Stein, Cinara; Colpani, Verônica; Barker, Timothy Hugh; Ziegelmann, Patricia Klarmann; Munn, Zachary; Falavigna, Maicon – Research Synthesis Methods, 2022
Over the last decade, there has been a 10-fold increase in the number of published systematic reviews of prevalence. In meta-analyses of prevalence, the summary estimate represents an average prevalence from included studies. This estimate is truly informative only if there is no substantial heterogeneity among the different contexts being pooled.…
Descriptors: Incidence, Meta Analysis, Statistics, Statistical Distributions
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Andrade, Luisa; Fernández, Felipe – Universal Journal of Educational Research, 2016
As literature has reported, it is usual that university students in statistics courses, and even statistics teachers, interpret the confidence level associated with a confidence interval as the probability that the parameter value will be between the lower and upper interval limits. To confront this misconception, class activities have been…
Descriptors: Conflict, College Students, Statistics, Probability
Letkowski, Jerzy – Journal of Case Studies in Education, 2014
Descripting Statistics provides methodology and tools for user-friendly presentation of random data. Among the summary measures that describe focal tendencies in random data, the mode is given the least amount of attention and it is frequently misinterpreted in many introductory textbooks on statistics. The purpose of the paper is to provide a…
Descriptors: Statistical Data, Data Interpretation, Statistics, Qualitative Research
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Blagdanic, Casandra; Chinnappan, Mohan – Australian Mathematics Teacher, 2013
Numeracy in schools is becoming an increasingly important part of mathematics learning and teaching. This is because educators want students to engage with mathematical concepts more deeply, use mathematics to make sense of their environment and make decisions that are based on the analysis of mathematical information. In order to be numerate,…
Descriptors: Statistical Analysis, Statistics, Data Interpretation, Numeracy
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Smith, Amy; Molinaro, Marco; Lee, Alisa; Guzman-Alvarez, Alberto – Science Teacher, 2014
For students to be successful in STEM, they need "statistical literacy," the ability to interpret, evaluate, and communicate statistical information (Gal 2002). The science and engineering practices dimension of the "Next Generation Science Standards" ("NGSS") highlights these skills, emphasizing the importance of…
Descriptors: STEM Education, Statistics, Statistical Analysis, Learning Modules
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Hoekstra, Rink; Johnson, Addie; Kiers, Henk A. L. – Educational and Psychological Measurement, 2012
The use of confidence intervals (CIs) as an addition or as an alternative to null hypothesis significance testing (NHST) has been promoted as a means to make researchers more aware of the uncertainty that is inherent in statistical inference. Little is known, however, about whether presenting results via CIs affects how readers judge the…
Descriptors: Computation, Statistical Analysis, Hypothesis Testing, Statistical Significance
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King, Douglas – Journal of Electronic Resources Librarianship, 2009
In answering the question "What is the next trend in usage statistics in libraries?" an eclectic group of respondents has presented an assortment of possibilities, suggestions, complaints and, of course, questions of their own. Undoubtedly, usage statistics collection, interpretation, and application are areas of growth and increasing complexity…
Descriptors: Trend Analysis, Library Research, Use Studies, Library Services
Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research
Bracey, Gerald W. – Education Digest: Essential Readings Condensed for Quick Review, 2006
It is curious that so many people are accepting of statistics despite Disraeli's famous aphorism concerning "three kinds of lies." This acceptance certainly seems to hold for education statistics, especially when they imply something negative about American public schools. Sometimes people accept statistics because they are not in a position to…
Descriptors: Data Interpretation, Statistics, Correlation, Rhetoric
Beins, Bernard C. – 1991
A study investigated the effect of writing in statistics classes on students' interpretation skills (translating the results of data analysis into verbal interpretations that are accessible to non-statisticians). One hundred twenty-two students in three statistics classes received either low, moderate, or high instructional emphasis in…
Descriptors: Content Area Writing, Data Interpretation, Educational Research, Higher Education
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Barbella, Peter; And Others – Mathematics Teacher, 1990
Demonstrates a statistically valid method allowing students to explore randomization. Described are two examples: counting techniques for a small set of data and simulation for a large sample. (YP)
Descriptors: Data Analysis, Data Interpretation, Mathematical Concepts, Mathematical Logic
Creighton, Theodore B. – 2000
Data collection and analysis are frequently neglected by school leaders over the course of the decision-making process. All schools gather large amounts of information about students and teachers, but most data are used to satisfy administrative requirements rather than evaluate school improvement in a systematic fashion. Apprehension regarding…
Descriptors: Administrator Education, Data, Data Analysis, Data Collection
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Goldstein, Miriam D.; Strube, Michael J. – Teaching of Psychology, 1995
Describes two QuickBASIC programs that provide students direct experience with interpreting correlation scatter-plots. Maintains that the programs can be used in classroom exercises to highlight factors that influence the size of a Pearson correlation coefficient. (CFR)
Descriptors: Computer Software Development, Computer Uses in Education, Correlation, Data Analysis
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Strube, Michael; Goldstein, Miriam D. – Teaching of Psychology, 1995
Describes a QuickBASIC program for demonstrating the differences between main effects and interactions in factorial designs. The program can be used in conjunction with a traditional lecture to improve student understanding and develop skills in recognizing main effects and interactions from graphic displays. (CFR)
Descriptors: Computer Software Development, Computer Uses in Education, Correlation, Data Analysis
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Bohmer, Susanne K. – Feminist Teacher, 1989
Addresses the problem in an introductory women's studies course of student resistance to generalizing statements that document inequality in society. Discusses a presentation made to the class on the importance of generalizations in understanding sociological and political research findings, including statistics. Maintains that objections to…
Descriptors: Bias, Course Content, Course Descriptions, Data Interpretation
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