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Showing 1 to 15 of 17 results Save | Export
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El-khateeb, Mahmoud M. A. – Journal of Education and Learning, 2015
The purpose of this study was to investigate the misperceptions and performance of king Saud University students' about concept and finding the limit of same partial functions given in the form of both graphical and symbolic. In the collection of the data, the researcher employed the open-ended question test consisted of four items. Firstly,…
Descriptors: Foreign Countries, College Students, Student Attitudes, Misconceptions
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Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
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Bird, Kevin D. – Psychological Methods, 2011
Any set of confidence interval inferences on J - 1 linearly independent contrasts on J means, such as the two comparisons [mu][subscript 1] - [mu][subscript 2] and [mu][subscript 2] - [mu][subscript 3] on 3 means, provides a basis for the deduction of interval inferences on all other contrasts, such as the redundant comparison [mu][subscript 1] -…
Descriptors: Intervals, Statistical Analysis, Inferences, Comparative Analysis
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Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2013
In education randomized control trials (RCTs), the misreporting of student outcome data could lead to biased estimates of average treatment effects (ATEs) and their standard errors. This article discusses a statistical model that adjusts for misreported binary outcomes for two-level, school-based RCTs, where it is assumed that misreporting could…
Descriptors: Control Groups, Experimental Groups, Educational Research, Data Analysis
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Schochet, Peter Z. – Society for Research on Educational Effectiveness, 2013
In randomized control trials (RCTs) of educational interventions, there is a growing literature on impact estimation methods to adjust for missing student outcome data using such methods as multiple imputation, the construction of nonresponse weights, casewise deletion, and maximum likelihood methods (see, for example, Allison, 2002; Graham, 2009;…
Descriptors: Control Groups, Experimental Groups, Educational Research, Data Analysis
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Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E. – Multivariate Behavioral Research, 2011
Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…
Descriptors: Personality Problems, Psychosis, Prevention, Patients
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Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2013
The 2012 edition of the "Digest of Education Statistics" is the 48th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: School Statistics, Definitions, Tables (Data), Longitudinal Studies
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Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2012
The 2011 edition of the "Digest of Education Statistics" is the 47th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: Educational Research, Data Collection, Data Analysis, Error Patterns
Love, Gloria C. – 1988
The probability of experiment-wise error is explored. Overall, the experiment-wise error rate is directly related to the test-wise error rate--the alpha level set by researchers to curtail the existence of a Type I error. A Type I error occurs when a true null hypothesis is rejected in a given study or experiment. The experiment-wise error rate is…
Descriptors: Data Analysis, Error Patterns, Estimation (Mathematics), Experiments
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Katz, Barry M.; McSweeney, Maryellen – Journal of Experimental Education, 1979
Errors of misclassification and their effects on categorical data analysis are discussed. The chi-square test for equality of two proportions is examined in the context of errorful categorical data. The effects of such errors are illustrated. A correction procedure is developed and discussed. (Author/MH)
Descriptors: Classification, Data Analysis, Data Collection, Error Patterns
St. Pierre, Robert G. – Evaluation Quarterly, 1978
Data from the national evaluation of Project Follow Through were analyzed using analysis of covariance with and without correcting the pretest for unreliability. Such corrections led to some changes in conclusions. There are many disagreements in the literature about the appropriateness of correction for unreliability. (Author/CTM)
Descriptors: Analysis of Covariance, Data Analysis, Error Patterns, Pretests Posttests
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Werts, C. E.; And Others – Educational and Psychological Measurement, 1976
A procedure is presented for the analysis of rating data with correlated intrajudge and uncorrelated interjudge measurement errors. Correlations between true scores on different rating dimensions, reliabilities for each judge on each dimension and correlations between intrajudge errors can be estimated given a minimum of three raters and two…
Descriptors: Correlation, Data Analysis, Error of Measurement, Error Patterns
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Croninger, Robert G.; Douglas, Karen M. – New Directions for Institutional Research, 2005
Many do not consider the effect that missing data have on their survey results nor do they know how to handle missing data. This chapter offers strategies for handling item-missing data and provides a practical example of how these strategies may affect results. The chapter concludes with recommendations for preventing and dealing with missing…
Descriptors: Institutional Research, Research Methodology, Surveys, Error of Measurement
Russ-Eft, Darlene F.; Brandt, David A. – 1982
Error profiles for the Fall Enrollment Survey of the Higher Education General Information Survey (HEGIS) were developed as part of an assessment of the quality of survey data. Three statistics were of particular interest: the count of full-time equivalent students, the breakdown by race/ethnicity, and the count of unclassified students. Attention…
Descriptors: Data Analysis, Data Collection, Enrollment Trends, Error Patterns
Tella, Alfred – 1976
For one important set of data, namely, the data on unemployment and employment collected by the Census Bureau in its monthly Current Population Survey (CPS), some information on nonsampling error is available that can be used to evaluate the regularly reported labor force figures. The paper is concerned with the nonsampling error that relates…
Descriptors: Business Cycles, Census Figures, Data Analysis, Employment Level
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