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John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
Cao, Wenhao; Siegel, Lianne; Zhou, Jincheng; Zhu, Motao; Tong, Tiejun; Chen, Yong; Chu, Haitao – Research Synthesis Methods, 2021
A reference interval provides a basis for physicians to determine whether a measurement is typical of a healthy individual. It can be interpreted as a prediction interval for a new individual from the overall population. However, a reference interval based on a single study may not be representative of the broader population. Meta-analysis can…
Descriptors: Meta Analysis, Statistical Analysis, Intervals, Computation
Noma, Hisashi; Hamura, Yasuyuki; Gosho, Masahiko; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…
Descriptors: Network Analysis, Meta Analysis, Regression (Statistics), Error of Measurement
Quinn, Anne – Mathematics Teacher, 2016
While looking for an inexpensive technology package to help students in statistics classes, the author found StatKey, a free Web-based app. Not only is StatKey useful for students' year-end projects, but it is also valuable for helping students learn fundamental content such as the central limit theorem. Using StatKey, students can engage in…
Descriptors: Statistics, Computer Oriented Programs, Technology Uses in Education, Teaching Methods
Schild, Anne H. E.; Voracek, Martin – Research Synthesis Methods, 2015
Research has shown that forest plots are a gold standard in the visualization of meta-analytic results. However, research on the general interpretation of forest plots and the role of researchers' meta-analysis experience and field of study is still unavailable. Additionally, the traditional display of effect sizes, confidence intervals, and…
Descriptors: Graphs, Visualization, Meta Analysis, Data Interpretation
Jance, Marsha L.; Thomopoulos, Nick T. – American Journal of Business Education, 2011
The paper shows how to find the min and max extreme interval values for the exponential and triangular distributions from the min and max uniform extreme interval values. Tables are provided to show the min and max extreme interval values for the uniform, exponential, and triangular distributions for different probabilities and observation sizes.
Descriptors: Intervals, Probability, Observation, Statistical Distributions
Chan, Wai – Educational and Psychological Measurement, 2009
A typical question in multiple regression analysis is to determine if a set of predictors gives the same degree of predictor power in two different populations. Olkin and Finn (1995) proposed two asymptotic-based methods for testing the equality of two population squared multiple correlations, [rho][superscript 2][subscript 1] and…
Descriptors: Multiple Regression Analysis, Intervals, Correlation, Computation
Jance, Marsha; Thomopoulos, Nick – American Journal of Business Education, 2009
The extreme interval values and statistics (expected value, median, mode, standard deviation, and coefficient of variation) for the smallest (min) and largest (max) values of exponentially distributed variables with parameter ? = 1 are examined for different observation (sample) sizes. An extreme interval value g[subscript a] is defined as a…
Descriptors: Intervals, Statistics, Predictor Variables, Sample Size
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
Lee, Won-Chan; Brennan, Robert L.; Kolen, Michael J. – Journal of Educational and Behavioral Statistics, 2006
Assuming errors of measurement are distributed binomially, this article reviews various procedures for constructing an interval for an individual's true number-correct score; presents two general interval estimation procedures for an individual's true scale score (i.e., normal approximation and endpoints conversion methods); compares various…
Descriptors: Probability, Intervals, Guidelines, Computer Simulation