Academia

Glossary – Royal Statistical Society – StatsLife – Definitions of Average; Statistical Significance; Standard Deviation; Regression Analysis; Regression to the Mean.

• Sampling – Why Sample? Types of Samples; Simple Random Sample; Systematic Random Sample; Stratified Random Sample; Cluster Sample; How Big a Sample Do I Need? Sample size formula; Sample size table; Sample Quality; Exercises – Professor Michelle A. Saint-Germain, Public Policy and Administration and Director, Program Review and Assement, California State University Long Beach
• Polls – Studies; The Random Sample; Selection Effects; Classic Example; How Gallup’s poll worked; American Idol Voting – Physics 3333 / CFB 3333 / The Scientific Method – Critical and Creative Thinking (Debunking Pseudoscience), Professor John L. Cotton and Professor Randall J. Scalise, Department of Physics – Southern Methodist University
• Sampling methods – The need for accurate information in order to make informed decisions is emphasized throughout this online publication (see the section on Data, information and statistics). Statistics are an important type of information and statistical agencies play an important part in producing such information. In order to do this, the agencies conduct censuses and sample surveys and use administrative records. These three types of data collection, along with their advantages and disadvantages, are explained in the Data collection section. Statistics Canada, a member of the Industry Portfolio, produces statistics that help Canadians better understand their country—its population, resources, economy, society and culture.

• Clickable diagram of distribution relationships – Probability distributions have a surprising number inter-connections. A dashed line in the chart below indicates an approximate (limit) relationship between two distribution families. A solid line indicates an exact relationship: special case, sum, or transformation.
• SticiGui – Philip B. Stark, Department of Statistics, University of California, Berkeley. This text was written for a “terminal” introductory class in Statistics suitable students in Business, Communications, Economics, Psychology, Social Science, or liberal arts; that is, this is the first and last class in Statistics for most students who take it. It also covers logic and reasoning at a level suitable for a general education course.
• Statistical Thinking for Managerial Decisions, Professor Hossein Arsham. This Web site is a course in statistics appreciation; i.e., acquiring a feeling for the statistical way of thinking. It contains various useful concepts and topics at many levels of learning statistics for decision making under uncertainties. The cardinal objective for this Web site is to increase the extent to which statistical thinking is merged with managerial thinking for good decision making under uncertainty.
• Probability and statistics EBook This is a General Statistics Curriculum E-Book, which includes Advanced-Placement (AP) materials. This is an Internet-based probability and statistics E-Book. The materials, tools and demonstrations presented in this E-Book would be very useful for advanced-placement (AP) statistics educational curriculum. The E-Book is initially developed by the UCLA Statistics Online Computational Resource (SOCR). However, all statistics instructors, researchers and educators are encouraged to contribute to this project and improve the content of these learning materials. There are 4 novel features of this specific Statistics EBook. It is community-built, completely open-access (in terms of use and contributions), blends information technology, scientific techniques and modern pedagogical concepts, and is multilingual.
• Sistema Galileu de Educação Estatística – O objetivo do Sistema Galileu de Educação Estatística é propiciar um ambiente de recursos Web de qualidade, interativo e de livre acesso, destinados ao aprendizado da estatística. Basicamente, consiste de uma biblioteca interligada de objetos de aprendizagem, cuja finalidade é a educação estatística. Os objetos são tópicos, verbetes e biografias na forma de hipertextos, além de conjuntos de dados, exemplos, atividades, tutoriais, programas estatísticos, apresentações e applets.
• Khan Academy – Watch. Practice. Learn almost anything for free. Will a library of over 2600 videos covering everything from arithmetic to physics, finance, and history and 218 practice exercises, we’re on a mission to help you learn what you want, when you want, at your own pace. [Muitos tópicos de estatística básica, cálculo, álgebra linear, entre outros, que podem ajudar o aluno no início dos cursos do bacharelado em estatística]
• Learning Statistics – by FreeStatistics.info – Free Statistical Software, Data and Resources
• eMathzone – Welcome to the Mathematics Zone for All. eMathzone proudly announces its first step towards math learning, which brings free education of math, its formulas & tools, solution of problems, measurment of your math skills and lot more…
• Statistical Advisor – Reference: StatSoft Online Textbook. Prepared By: Rajkumar BN (Draft version). Guia em PDF com orientações sobre as análises mais apropriadas dependendo do caso.

• Entenda a Teoria de Respostas ao Item (TRI), utilizada no Enem, Nota técnica de Camila Akemi Karino e Dalton Francisco de Andrade.
• Teoria da Resposta ao Item: Conceitos, Modelos e Aplicações, Prof. Dalton F. Andrade, Depto de Informática e Estatística – UFSC. Apresentação em PowerPoint.
• Item Response Theory (aka IRT) is also sometimes called latent trait theory. This is a modern test theory (as opposed to classical test theory). It is not the only modern test theory, but it is the most popular one and is currently an area of active research. IRT requires stronger assumptions than classical test theory (we will cover these in a moment). IRT is much intuitive approach to measurement once you get used to it. In IRT, the true score is defined on the latent trait of interest rather than on the test, as is the case in classical test theory. IRT is popular because it provides a theoretical justification for doing lots of things that classical test theory does not. Prof. Michael T. Brannick, University of South Florida, College of Arts and Sciences
• A Simple Guide to the Item Response Theory (IRT) and Rasch Modeling, Chong Ho Yu, Ph.Ds – This document, which is a practical introduction to Item Response Theory (IRT) and Rasch modeling, is composed of five parts: I. Item calibration and ability estimation, II. Item Characteristic Curve in one to three parameter models, III. Item Information Function and Test Information Function, IV. Item-Person Map, V. Misfit. Apresentação em PowerPoint.
• A visual guide to item response theory, Prof. Ivailo Partchev, Friedrich-Schiller-Universität Jena. 2004. (PDF)
• The Basics of Item Response Theory – Prof. Frank B. Baker, University of Wisconsin. (PDF)