NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Arzumanyan, George; Halcoussis, Dennis; Phillips, G. Michael – American Journal of Business Education, 2015
This paper presents the Agresti & Coull "Adjusted Wald" method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small…
Descriptors: Business Administration Education, Error of Measurement, Error Patterns, Intervals
Peer reviewed Peer reviewed
Direct linkDirect link
Le, Huy; Marcus, Justin – Educational and Psychological Measurement, 2012
This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…
Descriptors: Monte Carlo Methods, Probability, Mathematical Concepts, Effect Size
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Dimoliatis, Ioannis D. K.; Jelastopulu, Eleni – Universal Journal of Educational Research, 2013
The surgical theatre educational environment measures STEEM, OREEM and mini-STEEM for students (student-STEEM) comprise an up to now disregarded systematic overestimation (OE) due to inaccurate percentage calculation. The aim of the present study was to investigate the magnitude of and suggest a correction for this systematic bias. After an…
Descriptors: Educational Environment, Scores, Grade Prediction, Academic Standards
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