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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
Moreno, Samson Alexander – ProQuest LLC, 2017
Purpose: Four purposes were present in this journal-ready dissertation. The first purpose was to examine the degree to which the percentage of beginning teachers in traditionally configured elementary, middle, and secondary Texas schools differed as a function of two distinction designations (i.e., Academic Achievement in Reading/English Language…
Descriptors: Teacher Characteristics, Student Characteristics, Accountability, Beginning Teachers
Duran, Muharrem – International Journal of Environmental and Science Education, 2016
The aim of this study is to reveal differences between attitudes and approaches of students from different types of high school and the first grade of university towards problem solving in chemistry. For this purpose, the scale originally developed by Mason and Singh (2010) to measure students' attitude and approaches towards problem solving in…
Descriptors: High School Students, Student Attitudes, Problem Solving, Chemistry
Gelman, Andrew; Hill, Jennifer; Yajima, Masanao – Journal of Research on Educational Effectiveness, 2012
Applied researchers often find themselves making statistical inferences in settings that would seem to require multiple comparisons adjustments. We challenge the Type I error paradigm that underlies these corrections. Moreover we posit that the problem of multiple comparisons can disappear entirely when viewed from a hierarchical Bayesian…
Descriptors: Intervals, Comparative Analysis, Inferences, Error Patterns
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
Johnson, Clay Stephen – ProQuest LLC, 2013
Synthetic control methods are an innovative matching technique first introduced within the economics and political science literature that have begun to find application in educational research as well. Synthetic controls create an aggregate-level, time-series comparison for a single treated unit of interest for causal inference with observational…
Descriptors: Educational Assessment, Statistical Inference, Academic Achievement, Statistical Bias
Trumpower, David L. – Mathematical Thinking and Learning: An International Journal, 2013
Students' informal inferential reasoning (IIR) is often inconsistent with the normative logic underlying formal statistical methods such as Analysis of Variance (ANOVA), even after instruction. In two experiments reported here, student's IIR was assessed using an intuitive ANOVA task at the beginning and end of a statistics course. In both…
Descriptors: Statistical Analysis, Intuition, Inferences, Thinking Skills
What Works Clearinghouse, 2014
This "What Works Clearinghouse Procedures and Standards Handbook (Version 3.0)" provides a detailed description of the standards and procedures of the What Works Clearinghouse (WWC). The remaining chapters of this Handbook are organized to take the reader through the basic steps that the WWC uses to develop a review protocol, identify…
Descriptors: Educational Research, Guides, Intervention, Classification
Fan, Xitao; Nowell, Dana L. – Gifted Child Quarterly, 2011
This methodological brief introduces the readers to the propensity score matching method, which can be used for enhancing the validity of causal inferences in research situations involving nonexperimental design or observational research, or in situations where the benefits of an experimental design are not fully realized because of reasons beyond…
Descriptors: Research Design, Educational Research, Statistical Analysis, Inferences
Cribbie, Robert A. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…
Descriptors: Probability, Inferences, Structural Equation Models, Statistical Significance

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