Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 3 |
| Since 2017 (last 10 years) | 82 |
| Since 2007 (last 20 years) | 487 |
Descriptor
| Predictor Variables | 548 |
| Statistical Significance | 548 |
| Statistical Analysis | 197 |
| Correlation | 190 |
| Foreign Countries | 127 |
| Gender Differences | 114 |
| Academic Achievement | 108 |
| Regression (Statistics) | 107 |
| Multiple Regression Analysis | 99 |
| Scores | 94 |
| Questionnaires | 91 |
| More ▼ | |
Source
Author
| Borich, Gary D. | 3 |
| Pohlmann, John T. | 3 |
| Davis, Dawn H. | 2 |
| Fass-Holmes, Barry | 2 |
| Gordon, Howard R. D. | 2 |
| Huberty, Carl J. | 2 |
| Jaciw, Andrew | 2 |
| Pascarella, Ernest T. | 2 |
| Rapaport, Amie | 2 |
| Soria, Krista | 2 |
| Thompson, Bruce | 2 |
| More ▼ | |
Publication Type
Education Level
Audience
| Researchers | 6 |
| Policymakers | 2 |
| Teachers | 2 |
| Administrators | 1 |
Location
| Turkey | 21 |
| Texas | 19 |
| Jordan | 15 |
| Saudi Arabia | 11 |
| California | 10 |
| United States | 10 |
| North Carolina | 8 |
| Australia | 7 |
| Canada | 7 |
| Illinois | 7 |
| Maryland | 7 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
| Meets WWC Standards with or without Reservations | 1 |
| Does not meet standards | 5 |
Convey, John J. – 1975
The capability was studied of each of three models for producing indices that will reproduce school effectiveness rankings established a priori through simulation. The models used were a within-group regression technique, a regression model using individual scores, and a regression model using means. Data for 54 hypothetical schools on input, SES,…
Descriptors: Comparative Analysis, Correlation, Models, Predictor Variables
Huberty, Carl J. – 1971
This study was concerned with various schemes for reducing the number of variables in a multivariate analysis. Two sets of illustrative data were used; the numbers of criterion groups were 3 and 5. The proportion of correct classifications was employed as an index of discriminatory power of each subset of variables selected. Of the four procedures…
Descriptors: Cluster Analysis, Correlation, Criteria, Discriminant Analysis
Paszkowski, Diane M. – ProQuest LLC, 2008
Severe reductions in funding coupled with the imperative to measure and report teachers' ability to integrate technology into their practice pose a significant problem for school districts in New Jersey. This study was designed to identify factors that influence teacher use of technology. A review of the literature identified four areas of…
Descriptors: Technology Integration, Statistical Significance, Educational Technology, Data Analysis
Pascarella, Ernest T.; Cruce, Ty; Umbach, Paul D.; Wolniak, Gregory C.; Kuh, George D.; Carini, Robert M.; Hayek, John C.; Gonyea, Robert M.; Zhao, Chun-Mei – Journal of Higher Education, 2006
Academic selectivity plays a dominant role in the public's understanding of what constitutes institutional excellence or quality in undergraduate education. In this study, we analyzed two independent data sets to estimate the net effect of three measures of college selectivity on dimensions of documented good practices in undergraduate education.…
Descriptors: College Instruction, Selective Admission, Undergraduate Study, Educational Quality
Duggan, Joan G.; And Others – 1983
This paper is concerned with the identification and testing of salient variables which show potential for explaining client use of evaluation information. A single-page interview instrument was devised which aggregated the factors and factor categories collected following an extensive review of the literature. Data were collected from a…
Descriptors: Classification, Data Collection, Discriminant Analysis, Evaluation Utilization
Peer reviewedCohen, Patricia – Evaluation and Program Planning: An International Journal, 1982
The various costs of Type I and Type II errors of inference from data are discussed. Six methods for minimizing each error type are presented, which may be employed even after data collection for Type I and which minimizes Type II errors by a study design and analytical means combination. (Author/CM)
Descriptors: Analysis of Variance, Data Analysis, Data Collection, Error of Measurement
Lee, Joohi – Journal of Early Childhood Teacher Education, 2005
This study examined correlations between teachers' attitudes toward mathematics/teaching mathematics and the practice of developmentally appropriate mathematics. This study tested two independent variables: (1) kindergarten teachers' attitudes toward mathematics; and (2) kindergarten teachers' attitudes toward teaching mathematics; and their…
Descriptors: Predictor Variables, Statistical Significance, Kindergarten, Researchers
McGee, Glenn William – 1986
Although technological innovations have been widely adopted in elementary schools, efforts to implement these have generally not been successful. Past research on innovation has largely ignored the social context in which implementation occurs. This research examines how the implementation of the microcomputer is affected by the traditional social…
Descriptors: Adoption (Ideas), Analysis of Variance, Elementary Education, Elementary Schools
Vasu, Ellen S.; Elmore, Patricia B. – 1975
The effects of the violation of the assumption of normality coupled with the condition of multicollinearity upon the outcome of testing the hypothesis Beta equals zero in the two-predictor regression equation is investigated. A monte carlo approach was utilized in which three differenct distributions were sampled for two sample sizes over…
Descriptors: Correlation, Error of Measurement, Factor Structure, Hypothesis Testing
Manochehri, Nasar; Young, Jon I. – Quarterly Review of Distance Education, 2006
This study compared the effects student learning styles with Web-based learning (WBL) and traditional instructor-based learning (ILB) on student knowledge and satisfaction. Learning methods (Web-based and instructor-based) and learning styles (Diverger, Converger, Assimilator, and Accommodator) were the independent variables. Student knowledge and…
Descriptors: Cognitive Style, Learning Strategies, Web Based Instruction, Conventional Instruction
Schmitt, Neal – 1991
Detailed methodology used to evaluate a causal model of school environment is presented in this report. The model depicts societal features that influence school district values and organizational characteristics, which in turn influence school operations and personnel attitudes and values. These school variables affect school community members'…
Descriptors: Analysis of Variance, Causal Models, Correlation, Educational Environment
Birch, Elisa R.; Miller, Paul W. – Education Research and Perspectives, 2006
The Australian literature suggests that students' academic success in tertiary education is principally influenced by their university entrance score. Personal, secondary school and university characteristics have more minor impacts on tertiary outcomes. Little research has been undertaken into the relationship between students' marks and the…
Descriptors: Foreign Countries, Academic Achievement, Debt (Financial), College Students
Southern Association of Colleges and Schools Accreditation: Impact on Elementary Student Performance
Bruner, Darlene Y.; Brantley, Lance Lamar – Education Policy Analysis Archives, 2004
Currently, 848 Georgia public elementary schools that house third- and fifth-grades in the same building use the Southern Association of Colleges and Schools (SACS) accreditation as a school improvement model. The purpose of this investigation was to determine whether elementary schools that are SACS accredited increased their levels of academic…
Descriptors: Elementary Schools, Accreditation (Institutions), Achievement Gains, Academic Standards
Herbert, Michael – Online Journal of Distance Learning Administration, 2006
To appeal to a larger student base, institutions have utilized current online technologies to provide courses to those students who would not otherwise be served. Unfortunately, the online learning experience has not been a positive one for a substantial portion of participating students. Thus, a key issue for postsecondary institutions is that of…
Descriptors: Undergraduate Students, Online Courses, Academic Persistence, Student Satisfaction
Robey, Randall R.; Barcikowski, Robert S. – 1986
This paper reports the results of a Monte Carlo investigation of Type I errors in the single group repeated measures design where multiple measures are collected from each observational unit at each measurement occasion. The Type I error of three multivariate tests were examined. These were the doubly multivariate F test, the multivariate mixed…
Descriptors: Analysis of Variance, Behavioral Science Research, Comparative Analysis, Hypothesis Testing

Direct link
