Rice Virtual Lab in Statistics

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Referências úteis para conceitos de estatística básica.

HyperStat Online
An online statistics book with links to other statistics resources on the web.
Simulations/Demonstrations
Java applets that demonstrate various statistical concepts.
Case Studies
Examples of real data with analyses and interpretation
Analysis Lab
Some basic statistical analysis tools.

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Statistical Associates E-Book Catalog

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e-books grátis.

TITLE INFO DESCRIPTION EDITION FREE KINDLE
NO PASSWORD REQUIRED FOR TITLES IN THIS SECTION
2013 Annual Report, Statistical Associates Publishers Info Pages: 8. Coverage: General. 2013 Free No Kindle edition
10 Worst Statistical Mistakes and Pitfalls Info Coverage: For selected statistical procedures 2015 Free No Kindle edition
Creating Simulated Datasets Info Pages: 15. Coverage: General, SPSS. 2012 Free No Kindle edition
Game Theory Info Pages: 15. Coverage: General. 2012 Free No Kindle edition
Probability Info Pages: 15. Coverage: General, SPSS, SAS, Stata. 2013 Free No Kindle edition
Testing Statistical Assumptions Info Pages: 51. Coverage: General, SPSS. 2012 Free Coming
E-MONOGRAPHS: ALL $5 AT AMAZON/KINDLE
Association, Measures of Info Pages: 49. Coverage: General, SPSS. 2012 Free Buy at Amazon
Correlation Info Pages: 60. Coverage: General, SPSS, SAS, Stata. 2013 Free Buy at Amazon
Correspondence Analysis Info Pages: 37. Coverage: General, SPSS. 2012 Free Buy at Amazon
Crosstabulation Info Pages: 60. Coverage: General, SPSS, SAS, Stata. 2013 Free Buy at Amazon
Curve Fitting & Nonlinear Regression Info Pages: 53. Coverage: General, SPSS. 2012 Free Buy at Amazon
Discriminant Function Analysis Info Pages: 52. Coverage: General, SPSS. 2012 Free Buy at Amazon
Life Tables & Kaplan-Meier Analysis Info Pages: 32. Coverage: General, SPSS. 2012 Free Buy at Amazon
Literature Review in Research and Dissertation Writing Info Pages: 52. Coverage: General. 2013 Free Buy at Amazon
Multidimensional Scaling Info Pages: 55. Coverage: General, SPSS. 2012 Free Buy at Amazon
Network Analysis Info Pages: 35. Coverage: General, UCINET. 2012 Free Buy at Amazon
Ordinal Regression Info Pages: 93. Coverage: General, SPSS, SAS, Stata. 2014 Free Buy at Amazon
Parametric Survival Analysis (Event History Analysis) Info Pages: 64. Coverage: General, Stata, SAS. 2012 Free Buy at Amazon
Partial Correlation Info Pages: 40. Coverage: General, SPSS, SAS, Stata. 2014 Free Buy at Amazon
Path Analysis Info Pages: 81. Coverage: General, SPSS AMOS. SAS, Stata. 2014 Free Buy at Amazon
Power Analysis Info Pages: 36. Coverage: General, SPSS SamplePower, G*Power. 2012 Free Buy at Amazon
Probit Regression & Response Models Info Pages: 92. Coverage: General, SPSS. 2012 Free Buy at Amazon
Research Design Info Pages: 53. Coverage: General. 2013 Free Buy at Amazon
Scales and Measures Info Pages: 91. Coverage: General, SPSS, SAS, Stata, WINSTEPS, jMetric 2013 Free Buy at Amazon
Survey Research & Sampling Info Pages: 82. Coverage: General. 2013 Free Buy at Amazon
Two-Stage Least Squares Regression Info Pages: 45. Coverage: General, Stata, SPSS, SAS. 2013 Free Buy at Amazon
Variance Components Analysis Info Pages: 37. Coverage: General, SPSS, SAS. 2012 Free Buy at Amazon
WLS: Weighted Least Squares Regression Info Pages: 54. Coverage: General, SPSS, SAS, Stata. 2013 Free

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Electronic Statistics Textbook: StatSoft

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Uma referência muito completa sobre métodos estatísticos e de data mining.

Proper citation:

  • (Electronic Version): StatSoft, Inc. (2013). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com/textbook/.
  • (Printed Version): Hill, T. & Lewicki, P. (2007). STATISTICS: Methods and Applications. StatSoft, Tulsa, OK.

Overview of Elementary Concepts in Statistics. In this introduction, we will briefly discuss those elementary statistical concepts that provide the necessary foundations for more specialized expertise in any area of statistical data analysis. The selected topics illustrate the basic assumptions of most statistical methods and/or have been demonstrated in research to be necessary components of one’s general understanding of the “quantitative nature” of reality (Nisbet, et al., 1987). Because of space limitations, we will focus mostly on the functional aspects of the concepts discussed and the presentation will be very short.

Further information on each of those concepts can be found in the Introductory Overview and Examples sections of this manual and in statistical textbooks. Recommended introductory textbooks are: Kachigan (1986), and Runyon and Haber (1976); for a more advanced discussion of elementary theory and assumptions of statistics, see the classic books by Hays (1988), and Kendall and Stuart (1979).


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JStor – pesquisa de livros e artigos

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um site com muitos livros e revistas com temas variados.

Ithaka

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Scholarpedia

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Uma alternativa à weekepedia com suposta melhor qualidade.

Welcome to Scholarpedia

the peer-reviewed open-access encyclopedia,
where knowledge is curated by communities of experts

Disseminate: share your expertise with a global audience

Pioneer: write the first persistent online review in your area of specialization

Steward: supervise the development of articles in your field

Collaborate: work with expert scientists and scholars from around the world

Learn: gain experience with scholarly writing and editing

Publish: transform your writing into a peer-reviewed article

erts

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CRAN Task Views

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Uma lista de temas com uma descrição dos principais pacotes R ligados ao tema

CRAN Task Views

Bayesian Bayesian Inference
ChemPhys Chemometrics and Computational Physics
ClinicalTrials Clinical Trial Design, Monitoring, and Analysis
Cluster Cluster Analysis & Finite Mixture Models
DifferentialEquations Differential Equations
Distributions Probability Distributions
Econometrics Econometrics
Environmetrics Analysis of Ecological and Environmental Data
ExperimentalDesign Design of Experiments (DoE) & Analysis of Experimental Data
Finance Empirical Finance
Genetics Statistical Genetics
Graphics Graphic Displays & Dynamic Graphics & Graphic Devices & Visualization
HighPerformanceComputing High-Performance and Parallel Computing with R
MachineLearning Machine Learning & Statistical Learning
MedicalImaging Medical Image Analysis
MetaAnalysis Meta-Analysis
Multivariate Multivariate Statistics
NaturalLanguageProcessing Natural Language Processing
NumericalMathematics Numerical Mathematics
OfficialStatistics Official Statistics & Survey Methodology
Optimization Optimization and Mathematical Programming
Pharmacokinetics Analysis of Pharmacokinetic Data
Phylogenetics Phylogenetics, Especially Comparative Methods
Psychometrics Psychometric Models and Methods
ReproducibleResearch Reproducible Research
Robust Robust Statistical Methods
SocialSciences Statistics for the Social Sciences
Spatial Analysis of Spatial Data
SpatioTemporal Handling and Analyzing Spatio-Temporal Data
Survival Survival Analysis
TimeSeries Time Series Analysis
WebTechnologies Web Technologies and Services
gR gRaphical Models in R

To automatically install these views, the ctv package needs to be installed, e.g., via
install.packages("ctv")
library("ctv")
and then the views can be installed via install.views or update.views (which first assesses which of the packages are already installed and up-to-date), e.g.,
install.views("Econometrics")
or
update.views("Econometrics")

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Montes de recursos sobre R

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Muitos recursos para o R que vão de exemplos introdutórios até ao multivariado.

Do it yourself Introduction to R

R is a free statistical programming language environment. It is completely free to anyone — like the air you breath is free.

For more information on why everyone should be using R, see here.

The goal of this site is to allow someone to overcome the intimidation associated with learning the very basics of R and showing them the tools for continued usage. Let’s get started.

Some assumptions: This site assumes you are using a Windows operating system and have a basic understanding of file structures and paths. You will also need to have administrator privileges in order to install R. Some of the notes linked on this page are standard HTML pages; most of the links on this page are in R script file format (they have the file extension.R). Beyond that; the site and any instructions or links on it should be self-explanatory. It is STRONGLY recommended that one progress through the modules in order.

A brief explanation of this page is here.

UPDATE NOTE: April 23, 2015: current R version is 3.2.0

These pages have been tested for use with Firefox, other browsers may display the pages incorrectly.

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Using Open Source in Higher Education: R Tutorials

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Alguns bons tutoriais para aprender mais.

Recent Posts

Recent Comments

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Archives

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What is Data Virtualization?

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Muito clara introdução ao tema da virtualização de dados.

What is Data Virtualization?

5 882

0:00
Hi I’m Jared Hillam, There are a lot of parts and components that
0:04
go into accurately gathering data. However, at the heart of any well-crafted solution
0:10
is the data integration and query logic. This is the logic that tells the database what
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data is being requested and how to process it. Where that logic exists turns out to be
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a very important topic when all is said and done as you’ll find in this video. To illustrate
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this let me share with you an example. Many years ago I worked for a software company
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that sought out to fix a common problem found in Operational Reporting. We developed a product
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that allowed you to open 1000s of operational reports and edit all of them at once. Why

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An Example of R Versatility

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By Dave Collingridge

In my last blog post I mentioned a few advantages to learning R. One of those advantages is that R opens up a world of new data analyses. There are novel techniques available in R that are not found in the ANALYZE drop down menus of SPSS, Stata, and Statistica. Novel techniques in R can be a big help in situations where data are not well-suited for traditional analyses like t-tests, ANOVA, and regression.

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