Real Chart Rules to Follow

Posted by Armando Brito Mendes | Filed under estatística, materiais ensino, visualização

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Excelente guia sobre construção de gráficos para representar dados.

There are a lot of “rules” for visualization. Some are actual rules, and some are suggestions to help you make choices. Many of the former can be broken, if that’s what the data dictates and you know what you’re doing.

But, there are rules—usually for specific chart types meant to be read in a specific way and with few exceptions—that you shouldn’t break. When they are, everyone loses. This is that small handful.

Tags: data mining, definição, Estat Descritiva, R-software

Read more | Comments off | August 12th, 2015

Comprehensive Guide to Data Visualization in R

Posted by Armando Brito Mendes | Filed under estatística, visualização

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Bom resumo de alguns tipos de gráficos que podem ser obtidos no R, do mais simples a alguns mais complexos.

This visualization (originally created using Tableau) is a great example of how data visualization can help decision makers. Imagine telling this information to an investor through a table. How long do you think you will take to explain it to him?

With ever increasing volume of data in today’s world, it is impossible to tell stories without these visualizations. While there are dedicated tools like Tableau, QlikView and d3.js, nothing can replace a modeling / statistics tools with good visualization capability. It helps tremendously in doing any exploratory data analysis as well as feature engineering. This is where R offers incredible help.

R Programming offers a satisfactory set of inbuilt function and libraries (such as ggplot2, leaflet, lattice) to build visualizations and present data. In this article, I have covered the steps to create the common as well as advanced visualizations in R Programming.

Tags: análise de dados, data mining, Estat Descritiva, R-software, software estatístico

Read more | Comments off | August 10th, 2015

visualização do intervalo de confiança

Posted by Armando Brito Mendes | Filed under estatística, materiais ensino, visualização

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Boa forma de visualizar o conceito de Intervalo de Confiança Aleatório.

About the visualization

Some say that a shift from hypothesis testing to confidence intervals and estimation will lead to fewer statistical misinterpretations. Personally, I am not sure about that. But I agree with the sentiment that we should stop reducing statistical analysis to binary decision-making. The problem with CIs is that they are as unintuitive and as misunderstood p-values and null hypothesis significance testing. Moreover, CIs are often used to perform hypothesis tests and are therefore prone to the same misuses as p-values.

Tags: belo, definição, inferência

Read more | Comments off | June 29th, 2015

R news and tutorials R bloggers

Posted by Armando Brito Mendes | Filed under estatística, matemática, software

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Montes de blogs sobre R.

Here you will find daily news and tutorials about R, contributed by over 573 bloggers.

S-PLUS & R Class Links

Posted by Armando Brito Mendes | Filed under estatística, materiais ensino, materiais para profissionais, software

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montes de materiais para R e S-PLUS.

S-PLUS & R Class Links

Instructor: Richard Herrington

Why Do We Care To Use the “S” Language? Does anyone care besides us? The Association for Computing Machinery (ACM) cares

S-Plus

S-PLUS Student Edition Download (Free)

Student Edition 6.2 – This version of S-Plus has a 20,000 cell or 1,000 row limitation; is only for educational use; is good for only one year; and is a rather large download (100+ meg).

S-PLUS Free Experimental Libraries and User Contributed Libraries

Research Libraries – Includes: S+CorrelatedData (mixed effects generalized linear models), S+Best (B-Spline methods), S+Resample (bootstrap library), S+Bayes (bayesian analysis), S+FDA (functional data analysis).
User Contributed Libraries

Tinn-R Script Editor

SourceForge Download Site – Download Tinn-R Setup Files; Tinn-R can serve as a script editor and “pager” for R Console. See Tinn-R Convenient Script Editor for R on Win32 Platform

R

Download Site for the Current Windows Install Binary and R Packages

Main CRAN Website
CRAN Windows Binary – Installer for Win32 (also available for MacOS X and Linux
CRAN R Package Descriptions – Pdf manuals available for packages
R Packages Organized by Topic – Organized by discipline and methodology

Web Interfaces to R Web Servers and Example R Scripts

R Web Interfaces – Web/browser based interfaces to R script processing on a server
Example R Scripts – Some of these scripts run on a server and results are communicated thru a web browser
RSS Rweb Server – Link to http:/rss.acs.unt.edu R server

R, R(D)COM and Excel

Introduction to R – ppt
Using R with Excel – A (D)COM Server for the Windows Platform – Benchmarks article (needs updating badly – Rich)
R(D)COM Server Homepage – Thomas Baier
R(D)COM Listserve Archive
Download for single install file – R-2.4.1, R(D)COM and RExcel only
Download for single install file – R-2.4.1 – use this file for a comprehensive install of selectable components: R, Rcmdr, R(D)COM, RExcel, rcom, gobbi, Rgobbi, and Tinn-R. R Version 2.5.0 combined install found here.
Installing The R(D)COM server – Help Pages
Using The R(D)COM server – Help Pages
Using R Within Excel – Help Pages
Duncan Temple Lang’s R (D)COM Homepage
Duncan Temple Lang’s R (D)COM Notes
Duncan Temple Lang’s R (D)COM Client examples– directory listing
Duncan Temple Lang’s R (D)COM Server – examples listing
General Computing Considerations

Tags: Excel, R-software, software estatístico

Read more | Comments off | May 30th, 2015

Rtips. Revival 2014!

Posted by Armando Brito Mendes | Filed under estatística, matemática, software

Uma animação com todos os lugares referidos numa canção de johnny cash

Montes de exemplos de R numa única longa página.

Table of Contents

Section: Original Preface

Section 1: Data Input/Output

Subsection 1.1: Bring raw numbers into R (05/22/2012)

Subsection 1.2: Basic notation on data access (12/02/2012)

Subsection 1.3: Checkout the new Data Import/Export manual (13/08/2001)

Subsection 1.4: Exchange data between R and other programs (Excel, etc) (01/21/2009)

Subsection 1.5: Merge data frames (04/23/2004)

Subsection 1.6: Add one row at a time (14/08/2000)

Subsection 1.7: Need yet another different kind of merge for data frames (11/08/2000)

Subsection 1.8: Check if an object is NULL (06/04/2001)

Subsection 1.9: Generate random numbers (12/02/2012)

Subsection 1.10: Generate random numbers with a fixed mean/variance (06/09/2000)

Subsection 1.11: Use rep to manufacture a weighted data set (30/01/2001)

Subsection 1.12: Convert contingency table to data frame (06/09/2000)

Subsection 1.13: Write: data in text file (31/12/2001)

Section 2: Working with data frames: Recoding, selecting, aggregating

Subsection 2.1: Add variables to a data frame (or list) (02/06/2003)

Subsection 2.2: Create variable names on the fly (10/04/2001)

Subsection 2.3: Recode one column, output values into another column (12/05/2003)

Subsection 2.4: Create indicator (dummy) variables (20/06/2001)

Subsection 2.5: Create lagged values of variables for time series regression (05/22/2012)

Subsection 2.6: How to drop factor levels for datasets that don’t have observations with those values? (08/01/2002)

Subsection 2.7: Select/subset observations out of a dataframe (08/02/2012)

Subsection 2.8: Delete first observation for each element in a cluster of observations (11/08/2000)

Subsection 2.9: Select a random sample of data (11/08/2000)

Subsection 2.10: Selecting Variables for Models: Don’t forget the subset function (15/08/2000)

Subsection 2.11: Process all numeric variables, ignore character variables? (11/02/2012)

Subsection 2.12: Sorting by more than one variable (06/09/2000)

Subsection 2.13: Rank within subgroups defined by a factor (06/09/2000)

Subsection 2.14: Work with missing values (na.omit, is.na, etc) (15/01/2012)

Subsection 2.15: Aggregate values, one for each line (16/08/2000)

Subsection 2.16: Create new data frame to hold aggregate values for each factor ()

Subsection 2.17: Selectively sum columns in a data frame (15/01/2012)

Subsection 2.18: Rip digits out of real numbers one at a time (11/08/2000)

Subsection 2.19: Grab an item from each of several matrices in a List (14/08/2000)

Subsection 2.20: Get vector showing values in a dataset (10/04/2001)

Subsection 2.21: Calculate the value of a string representing an R command (13/08/2000)

Subsection 2.22: Which can grab the index values of cases satisfying a test ()

Subsection 2.23: Find unique lines in a matrix/data frame (31/12/2001)

Section 3: Matrices and vector operations

Subsection 3.1: Create a vector, append values (01/02/2012)

Subsection 3.2: How to create an identity matrix? (16/08/2000)

Subsection 3.3: Convert matrix m to one long vector (11/08/2000)

Subsection 3.4: Creating a peculiar sequence (1 2 3 4 1 2 3 1 2 1) (11/08/2000)

Subsection 3.5: Select every n’th item (14/08/2000)

Subsection 3.6: Find index of a value nearest to 1.5 in a vector (11/08/2000)

Subsection 3.7: Find index of nonzero items in vector (18/06/2001)

Subsection 3.8: Find index of missing values (15/08/2000)

Subsection 3.9: Find index of largest item in vector (16/08/2000)

Subsection 3.10: Replace values in a matrix (22/11/2000)

Subsection 3.11: Delete particular rows from matrix (06/04/2001)

Subsection 3.12: Count number of items meeting a criterion (01/05/2005)

Subsection 3.13: Compute partial correlation coefficients from correlation matrix ()

Subsection 3.14: Create a multidimensional matrix (R array) (20/06/2001)

Subsection 3.15: Combine a lot of matrices (20/06/2001)

Subsection 3.16: Create neighbor matrices according to specific logics (20/06/2001)

Subsection 3.17: Matching two columns of numbers by a key variable (20/06/2001)

Subsection 3.18: Create Upper or Lower Triangular matrix (06/08/2012)

Subsection 3.19: Calculate inverse of X (12/02/2012)

Subsection 3.20: Interesting use of Matrix Indices (20/06/2001)

Subsection 3.21: Eigenvalues example (20/06/2001)

Section 4: Applying functions, tapply, etc

Subsection 4.1: Return multiple values from a function (12/02/2012)

Subsection 4.2: Grab ‘‘p’’ values out of a list of significance tests (22/08/2000)

Subsection 4.3: ifelse usage (12/02/2012)

Subsection 4.4: Apply to create matrix of probabilities, one for each cell (14/08/2000)

Subsection 4.5: Outer. (15/08/2000)

Subsection 4.6: Check if something is a formula/function (11/08/2000)

Subsection 4.7: Optimize with a vector of variables (11/08/2000)

Subsection 4.8: slice.index, like in S+ (14/08/2000)

Section 5: Graphing

Subsection 5.1: Adjust features with par before graphing (18/06/2001)

Subsection 5.2: Save graph output (03/21/2014)

Subsection 5.3: How to automatically name plot output into separate files (10/04/2001)

Subsection 5.4: Control papersize (15/08/2000)

Subsection 5.5: Integrating R graphs into documents: LaTeX and EPS or PDF (20/06/2001)

Subsection 5.6: ‘‘Snapshot’’ graphs and scroll through them (31/12/2001)

Subsection 5.7: Plot a density function (eg. Normal) (22/11/2000)

Subsection 5.8: Plot with error bars (11/08/2000)

Subsection 5.9: Histogram with density estimates (14/08/2000)

Subsection 5.10: How can I ‘‘overlay’’ several line plots on top of one another? (09/29/2005)

Subsection 5.11: Create ‘‘matrix’’ of graphs (18/06/2001)

Subsection 5.12: Combine lines and bar plot? (07/12/2000)

Subsection 5.13: Regression scatterplot: add fitted line to graph (03/20/2014)

Subsection 5.14: Control the plotting character in scatterplots? (11/08/2000)

Subsection 5.15: Scatterplot: Control Plotting Characters (men vs women, etc)} (11/11/2002)

Subsection 5.16: Scatterplot with size/color adjustment (12/11/2002)

Subsection 5.17: Scatterplot: adjust size according to 3rd variable (06/04/2001)

Subsection 5.18: Scatterplot: smooth a line connecting points (02/06/2003)

Subsection 5.19: Regression Scatterplot: add estimate to plot (18/06/2001)

Subsection 5.20: Axes: controls: ticks, no ticks, numbers, etc (22/11/2000)

Subsection 5.21: Axes: rotate labels (06/04/2001)

Subsection 5.22: Axes: Show formatted dates in axes (06/04/2001)

Subsection 5.23: Axes: Reverse axis in plot (12/02/2012)

Subsection 5.24: Axes: Label axes with dates (11/08/2000)

Subsection 5.25: Axes: Superscript in axis labels (11/08/2000)

Subsection 5.26: Axes: adjust positioning (31/12/2001)

Subsection 5.27: Add ‘‘error arrows’’ to a scatterplot (30/01/2001)

Subsection 5.28: Time Series: how to plot several ‘‘lines’’ in one graph? (06/09/2000)

Subsection 5.29: Time series: plot fitted and actual data (11/08/2000)

Subsection 5.30: Insert text into a plot (22/11/2000)

Subsection 5.31: Plotting unbounded variables (07/12/2000)

Subsection 5.32: Labels with dynamically generated content/math markup (16/08/2000)

Subsection 5.33: Use math/sophisticated stuff in title of plot (11/11/2002)

Subsection 5.34: How to color-code points in scatter to reveal missing values of 3rd variable? (15/08/2000)

Subsection 5.35: lattice: misc examples (12/11/2002)

Subsection 5.36: Make 3d scatterplots (11/08/2000)

Subsection 5.37: 3d contour with line style to reflect value (06/04/2001)

Subsection 5.38: Animate a Graph! (13/08/2000)

Subsection 5.39: Color user-portion of graph background differently from margin (06/09/2000)

Subsection 5.40: Examples of graphing code that seem to work (misc) (11/16/2005)}

Section 6: Common Statistical Chores

Subsection 6.1: Crosstabulation Tables (01/05/2005)

Subsection 6.2: t-test (18/07/2001)

Subsection 6.3: Test for Normality (31/12/2001)

Subsection 6.4: Estimate parameters of distributions (12/02/2012)

Subsection 6.5: Bootstrapping routines (14/08/2000)

Subsection 6.6: BY subgroup analysis of data (summary or model for subgroups)(06/04/2001)

Section 7: Model Fitting (Regression-type things)

Subsection 7.1: Tips for specifying regression models (12/02/2002)

Subsection 7.2: Summary Methods, grabbing results inside an output object

Subsection 7.3: Calculate separate coefficients for each level of a factor (22/11/2000)

Subsection 7.4: Compare fits of regression models (F test subset B’s =0) (14/08/2000)

Subsection 7.5: Get Predicted Values from a model with predict() (11/13/2005)

Subsection 7.6: Polynomial regression (15/08/2000)

Subsection 7.7: Calculate p value for an F stat from regression (13/08/2000)

Subsection 7.8: Compare fits (F test) in stepwise regression/anova (11/08/2000)

Subsection 7.9: Test significance of slope and intercept shifts (Chow test?)

Subsection 7.10: Want to estimate a nonlinear model? (11/08/2000)

Subsection 7.11: Quasi family and passing arguments to it. (12/11/2002)

Subsection 7.12: Estimate a covariance matrix (22/11/2000)

Subsection 7.13: Control number of significant digits in output (22/11/2000)

Subsection 7.14: Multiple analysis of variance (06/09/2000)

Subsection 7.15: Test for homogeneity of variance (heteroskedasticity) (12/02/2012)

Subsection 7.16: Use nls to estimate a nonlinear model (14/08/2000)

Subsection 7.17: Using nls and graphing things with it (22/11/2000)

Subsection 7.18: and hypo tests (22/11/2000)

Subsection 7.19: logistic regression with repeated measurements (02/06/2003)

Subsection 7.20: Logit (06/04/2001)

Subsection 7.21: Random parameter (Mixed Model) tips (01/05/2005)

Subsection 7.22: Time Series: basics (31/12/2001)

Subsection 7.23: Time Series: misc examples (10/04/2001)

Subsection 7.24: Categorical Data and Multivariate Models (04/25/2004)

Subsection 7.25: Lowess. Plot a smooth curve (04/25/2004)

Subsection 7.26: Hierarchical/Mixed linear models. (06/03/2003)

Subsection 7.27: Robust Regression tools (07/12/2000)

Subsection 7.28: Durbin-Watson test (10/04/2001)

Subsection 7.29: Censored regression (04/25/2004)

Section 8: Packages

Subsection 8.1: What packages are installed on Paul’s computer?

Subsection 8.2: Install and load a package

Subsection 8.3: List Loaded Packages

Subsection 8.4: Where is the default R library folder? Where does R look for packages in a computer?

Subsection 8.5: Detach libraries when no longer needed (10/04/2001)

Section 9: Misc. web resources

Subsection 9.1: Navigating R Documentation (12/02/2012)

Subsection 9.2: R Task View Pages (12/02/2012)

Subsection 9.3: Using help inside R(13/08/2001)

Subsection 9.4: Run examples in R (10/04/2001)

Section 10: R workspace

Subsection 10.1: Writing, saving, running R code (31/12/2001)

Subsection 10.2: .RData, .RHistory. Help or hassle? (31/12/2001)

Subsection 10.3: Save & Load R objects (31/12/2001)

Subsection 10.4: Reminders for object analysis/usage (11/08/2000)

Subsection 10.5: Remove objects by pattern in name (31/12/2001)

Subsection 10.6: Save work/create a Diary of activity (31/12/2001)

Subsection 10.7: Customized Rprofile (31/12/2001)

Section 11: Interface with the operating system

Subsection 11.1: Commands to system like change working directory (22/11/2000)

Subsection 11.2: Get system time. (30/01/2001)

Subsection 11.3: Check if a file exists (11/08/2000)

Subsection 11.4: Find files by name or part of a name (regular expression matching) (14/08/2001)

Section 12: Stupid R tricks: basics you can’t live without

Subsection 12.1: If you are asking for help (12/02/2012)

Subsection 12.2: Commenting out things in R files (15/08/2000)

Section 13: Misc R usages I find interesting

Subsection 13.1: Character encoding (01/27/2009)

Subsection 13.2: list names of variables used inside an expression (10/04/2001)

Subsection 13.3: R environment in side scripts (10/04/2001)

Subsection 13.4: Derivatives (10/04/2001)

Tags: análise de dados, Estat Descritiva, inferência, R-software, software estatístico

Read more | Comments off | May 30th, 2015

Rice Virtual Lab in Statistics

Posted by Armando Brito Mendes | Filed under estatística, materiais ensino

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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.

Tags: Estat Descritiva, inferência

Read more | Comments off | May 29th, 2015

Statistical Associates E-Book Catalog

Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, matemática, materiais ensino

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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

Tags: data mining, motores de busca

Read more | Comments off | May 29th, 2015

Electronic Statistics Textbook: StatSoft

Posted by Armando Brito Mendes | Filed under estatística, materiais ensino, refs bibliográficas

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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).

Tags: análise de dados, data mining, Estat Descritiva, qualidade

Read more | Comments off | May 29th, 2015

Scholarpedia

Posted by Armando Brito Mendes | Filed under estatística, matemática, materiais para profissionais, refs bibliográficas

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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

Established faculty and researchers

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

Students and writers

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

Tags: data mining, motores de busca

Read more | Comments off | May 29th, 2015

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Armando B. Mendes

Real Chart Rules to Follow

Comprehensive Guide to Data Visualization in R

visualização do intervalo de confiança

About the visualization

R news and tutorials R bloggers

Top 3 Posts from the past 2 days

Top 9 articles of the week

S-PLUS & R Class Links

S-PLUS & R Class Links

Tinn-R Script Editor

R

Rtips. Revival 2014!

Rice Virtual Lab in Statistics

Statistical Associates E-Book Catalog

Electronic Statistics Textbook: StatSoft

Scholarpedia

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Students and writers

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