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Jane E. Miller – Numeracy, 2023
Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…
Descriptors: Statistical Significance, Holistic Approach, Statistical Inference, Effect Size
Oleson, Jacob J.; Brown, Grant D.; McCreery, Ryan – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Clinicians depend on the accuracy of research in the speech, language, and hearing sciences to improve assessment and treatment of patients with communication disorders. Although this work has contributed to great advances in clinical care, common statistical misconceptions remain, which deserve closer inspection in the field. Challenges…
Descriptors: Statistics, Speech Language Pathology, Research, Statistical Analysis
Rosenthal, Jeffrey S. – Teaching Statistics: An International Journal for Teachers, 2018
This article advocates that introductory statistics be taught by basing all calculations on a single simple margin-of-error formula and deriving all of the standard introductory statistical concepts (confidence intervals, significance tests, comparisons of means and proportions, etc) from that one formula. It is argued that this approach will…
Descriptors: Statistics, Introductory Courses, Computation, Statistical Analysis
Lane, David; Oswald, Frederick L. – Educational Measurement: Issues and Practice, 2016
The educational literature, the popular press, and educated laypeople have all echoed a conclusion from the book "Academically Adrift" by Richard Arum and Josipa Roksa (which has now become received wisdom), namely, that 45% of college students showed no significant gains in critical thinking skills. Similar results were reported by…
Descriptors: College Students, Critical Thinking, Thinking Skills, Statistical Analysis
Raykov, Tenko; Marcoulides, George A.; Tong, Bing – Educational and Psychological Measurement, 2016
A latent variable modeling procedure is discussed that can be used to test if two or more homogeneous multicomponent instruments with distinct components are measuring the same underlying construct. The method is widely applicable in scale construction and development research and can also be of special interest in construct validation studies.…
Descriptors: Models, Statistical Analysis, Measurement Techniques, Factor Analysis
Seastrom, Marilyn – Institute of Education Sciences, 2017
The Every Student Succeeds Act (ESSA) of 2015 (Public Law 114-95) requires each state to create a plan for its statewide accountability system. In particular, ESSA calls for state plans that include strategies for reporting education outcomes by grade for all students and for economically disadvantaged students, students from major racial and…
Descriptors: Accountability, Best Practices, Information Security, Sample Size
Raykov, Tenko; Marcoulides, George A.; Millsap, Roger E. – Educational and Psychological Measurement, 2013
A multiple testing method for examining factorial invariance for latent constructs evaluated by multiple indicators in distinct populations is outlined. The procedure is based on the false discovery rate concept and multiple individual restriction tests and resolves general limitations of a popular factorial invariance testing approach. The…
Descriptors: Testing, Statistical Analysis, Factor Analysis, Statistical Significance
McBee, Matthew T.; Matthews, Michael S. – Journal of Advanced Academics, 2014
The self-correcting nature of psychological and educational science has been seriously questioned. Recent special issues of "Perspectives on Psychological Science" and "Psychology of Aesthetics, Creativity, and the Arts" have roundly condemned current organizational models of research and dissemination and have criticized the…
Descriptors: Statistical Analysis, Periodicals, Replication (Evaluation), Hypothesis Testing
Hightower, Christy; Scott, Kerry – Issues in Science and Technology Librarianship, 2012
Many librarians use data from surveys to make decisions about how to spend money or allocate staff, often making use of popular online tools like Survey Monkey. In this era of reduced budgets, low staffing, stiff competition for new resources, and increasingly complex choices, it is especially important that librarians know how to get strong,…
Descriptors: Librarians, Surveys, Statistical Inference, Statistics
Liu, Xiaofeng Steven – International Journal of Mathematical Education in Science and Technology, 2012
The statistical power of a significance test is closely related to the length of the confidence interval (i.e. estimate precision). In the case of a "Z" test, the length of the confidence interval can be expressed as a function of the statistical power. (Contains 1 figure and 1 table.)
Descriptors: Statistical Analysis, Intervals, Statistical Significance, Statistics
Essawi, Mohammad; Abu-Hussain, Jamal; Fadila, Dalia – International Journal of Higher Education, 2014
The proposed intervention program's aim was to change teacher trainers' attitudes towards universal values. The program takes into account the unique cultural context of the developing society. The goal of the program was to reduce the gap between declared teacher trainers' attitudes and their actual attitudes towards universal values in the…
Descriptors: Foreign Countries, Developing Nations, Teacher Educator Education, Teacher Educators
Tennessee Higher Education Commission, 2012
The Tennessee General Assembly passed legislation in 2007 requiring that the State Board of Education produce an assessment on the effectiveness of teacher training programs. The law requires that the report include data on the performance of each program's graduates in the following areas: placement and retention rates, Praxis II results, and…
Descriptors: Program Effectiveness, Teacher Evaluation, Praxis, Academic Achievement
LeMire, Steven D. – Journal of Statistics Education, 2010
This paper proposes an argument framework for the teaching of null hypothesis statistical testing and its application in support of research. Elements of the Toulmin (1958) model of argument are used to illustrate the use of p values and Type I and Type II error rates in support of claims about statistical parameters and subject matter research…
Descriptors: Hypothesis Testing, Relationship, Statistical Significance, Models
Fan, Xitao; Nowell, Dana L. – Gifted Child Quarterly, 2011
This methodological brief introduces the readers to the propensity score matching method, which can be used for enhancing the validity of causal inferences in research situations involving nonexperimental design or observational research, or in situations where the benefits of an experimental design are not fully realized because of reasons beyond…
Descriptors: Research Design, Educational Research, Statistical Analysis, Inferences
Hemphill, F. Cadelle; Vanneman, Alan – National Center for Education Statistics, 2011
This report provides detailed information on the size of the achievement gaps between Hispanic and White public school students at the national and state levels and describes how those achievement gaps have changed over time. Additional information about race/ethnicity in NAEP is given in Appendix A. Most of the data in this report is derived from…
Descriptors: Achievement Gap, Public Schools, Family Income, Lunch Programs