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Kohr, Richard L.; Games, Paul A. – Journal of Experimental Education, 1974
The present study was addressed to the group AOV situation. Onte Carlo methods were employed to contrast several procedures with respect to a. ) control over Type 1 errors and b. ) power. (Editor)
Descriptors: Analysis of Variance, Data Analysis, Research Methodology, Sampling
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Moy, Mabel L. Y.; Barcikowski, Robert S. – Journal of Experimental Education, 1974
The purpose of this study was to help determine optimum item sampling plans for use in school evaluation projects. (Author)
Descriptors: Data Analysis, Evaluation Methods, Guidelines, Item Sampling
Keesling, J. Ward – 1973
In many circumstances it is appropriate to use the school as the unit of analysis. The variables measured on students must be aggregated to form a mean for each school. However, the means derived from the students sampled in a school will tend to fluctuate around the true mean for the school in a way determined by the within-school correlations…
Descriptors: Analysis of Covariance, Data Analysis, Males, Mathematical Models
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Rooks, Evelyn; King, Karl – Adolescence, 1973
This study had two purposes: first, to determine whether there exists a relationship between sex, family structure, power structure in the family of orientation, or social class and the kind of marriage role expectations of adolescents and to determine if those expectations are equalitarian. (Author/RK)
Descriptors: Adolescents, Blacks, Data Analysis, Expectation
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Lewy, Arieh – Educational Evaluation and Policy Analysis, 1981
Serial Evaluation Activities (SEAs) are series' of focused evaluational studies, each dealing with a well-defined "component unit" within a complex project. Strategies for enhancing timeliness in SEAs include a comprehensive conceptual framework, a permanent institutional setting, a prearranged sample plan, utilization of item banks, and…
Descriptors: Data Analysis, Institutional Research, Item Banks, Program Evaluation
Lawrence, Janet H.; Hendricks, Lori A.; Ott, Molly C. – Online Submission, 2007
The main goal of the Faculty Perceptions of Intercollegiate Athletics Survey is to examine professors' beliefs about and satisfaction with intercollegiate athletics. The investigation also identifies faculty members' primary concerns about intercollegiate athletics and gathers preliminary data on whether they would join campus-based initiatives…
Descriptors: College Athletics, College Faculty, Teacher Attitudes, Teacher Surveys
Herman, Joan L.; Yamashiro, Kyo; Lefkowitz, Sloane; Trusela, Lee Ann – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2008
This study examined the relationship between data use and achievement at 13 urban Title I schools. Using multiple methods, including test scores, district surveys, school transformation plans, and four case study site visits, the researchers found wide variation in the use of data to inform instruction and planning. In some cases, schools were …
Descriptors: Academic Achievement, Program Effectiveness, Scores, Data Analysis
Boser, Judith A. – 1988
This paper helps researchers develop criteria for conducting surveys. Cost considerations frame the paper's suggestions. Specifically, the text advises that researchers consider the human and material resources needed, type of survey instrument, medium for conducting the survey (mail, telephone, personal interview, etc.), data analysis…
Descriptors: Costs, Data Analysis, Educational Assessment, Evaluation Methods
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Barfield, Vivian; Burlingame, Martin – Journal of Experimental Education, 1974
The primary purpose of this study was to explore the relationship between the teacher's perception of pupil control and three particular variables, namely, the socioeconomic status of the school's clientele, the teacher's sense of efficacy, and the bureaucratic level of the school (elementary, junior, or senior).
Descriptors: Data Analysis, Perception, Sampling, Socioeconomic Status
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Hettmansperger, Thomas P. – Psychometrika, 1975
Treats the problem of testing an ordered hypothesis based on the ranks of the data. Statistical procedures for the randomized block design with more than one observation per cell are derived. Multiple comparisions and estimation procedures are included. (Author/RC)
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Nonparametric Statistics
Baumel, C. Phillip; And Others – 1964
A general guide to organizing and conducting reliable and useful community surveys is reported. Organization for the survey involves identifying and contacting relevant community groups, and meeting with organizational representatives. Constructing a questionnaire involves careful wording and ordering of questions, and determining if questions…
Descriptors: Community Organizations, Community Surveys, Data Analysis, Guidelines
Hsu, Tse-Chi; Feldt, Leonard S. – Amer Educ Res J, 1969
Descriptors: Analysis of Variance, Data Analysis, Ratios (Mathematics), Sampling
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Parker, Richard I. – Behavior Therapy, 2006
There is need for objective and reliable single-case research (SCR) results in the movement toward evidence-based interventions (EBI), for inclusion in meta-analyses, and for funding accountability in clinical contexts. Yet SCR deals with data that often do not conform to parametric data assumptions and that yield results of low reliability. A…
Descriptors: Data Analysis, Research Design, Intervention, Correlation
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Postlewaite, T. Neville – Comparative Education Review, 1974
The aim of this article is to give some basic information on the IEA survey in science, reading comprehension and literature so that the scene is set for the reader to understand the terminology and procedures reported in the articles which follow. (Author)
Descriptors: Cognitive Tests, Data Analysis, Educational Attitudes, Questionnaires
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Lewis, Charles; And Others – Psychometrika, 1975
A Bayesian Model II approach to the estimation of proportions in m groups is extended to obtain posterior marginal distributions for the proportions. The approach is extended to allow greater use of prior information than previously and the specification of this prior information is discussed. (Author/RC)
Descriptors: Bayesian Statistics, Data Analysis, Individualized Instruction, Models
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