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It covers statistical methods and applied statistics in the educational and behavioral sciences. The journal was established in 1976 as the Journal of Educational Statistics and obtained its current name in 1994. The journal's editors are Steven Andrew Culpepper (University of Illinois at Urbana-Champaign) and Gongjun Xu (University of Michigan ...
The GAISE College Report begins by synthesizing the history and current understanding of introductory statistics courses and then lists goals for students based on statistical literacy. [13] Six recommendations for introductory statistics courses are given, namely: [14] Emphasize statistical thinking and literacy over other outcomes
Journal for the Education of the Gifted; Journal of Early Intervention; Journal of Learning Disabilities; Journal of Research in Special Educational Needs; Journal of Special Education and Rehabilitation; Learning Disability Quarterly; Remedial and Special Education; Research and Practice for Persons with Severe Disabilities
Statistics education is the practice of teaching and learning of statistics, along with the associated scholarly research.. Statistics is both a formal science and a practical theory of scientific inquiry, and both aspects are considered in statistics education.
Educational research refers to the systematic collection and analysis of evidence and data related to the field of education. Research may involve a variety of methods [ 1 ] [ 2 ] [ 3 ] and various aspects of education including student learning, interaction, teaching methods , teacher training, and classroom dynamics.
The methods used in analytical studies encourage the exploration of mechanisms through multifactor designs, contextual variables introduced through blocking and replication over time. [3] This distinction between enumerative and analytic studies is the theory behind the Fourteen Points for Management. Dr.
In statistics education, informal inferential reasoning (also called informal inference) refers to the process of making a generalization based on data (samples) about a wider universe (population/process) while taking into account uncertainty without using the formal statistical procedure or methods (e.g. P-values, t-test, hypothesis testing, significance test).
For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. It is this second step which makes the technique one of non-probability sampling. In quota sampling the selection of the sample is non-random. For example, interviewers might be tempted to interview those who look most helpful.