What’s your kind of beer?
Posted by Armando Brito Mendes | Filed under estatística, visualização
Um bom exemplo de um site cheio de visualizações tipo dashboard
What’s your kind of beer?
Choose your preferred beer strength to begin exploring similar beers.
Explore Similar Beers by:
- Overall
- Aroma
- Taste
- Appearance
About the Data
Popularity and top beer styles are based on the number of users who rated the beer.
Tags: belo
Read Histograms and Use Them in R
Posted by Armando Brito Mendes | Filed under estatística, materiais para profissionais, visualização
Bom tutorial para construir histogramas no R
How to Read Histograms and Use Them in R
The histogram is one of my favorite chart types, and for analysis purposes, I probably use them the most. Devised by Karl Pearson (the father of mathematical statistics) in the late 1800s, it’s simple geometrically, robust, and allows you to see the distribution of a dataset.
If you don’t understand what’s driving the chart though, it can be confusing, which is probably why you don’t see it often in general publications.
Tags: análise de dados, data mining, Estat Descritiva, R-software, software estatístico
IFORS Simulation
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, materiais ensino
Algoritmos e Problemas de Simulação
The following 6 pages are in this category, out of 6 total.
D
E
M
S
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Tags: otimização, software de otimização
IFORS Education Resources Project
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, SAD - DSS, software
portal com materal sobre Investigação Operacional, otimização e SADs
Welcome to the International Federation of Operational Research Societies (IFORS) Education Resources Project
- Main Page (19:13, 3 December 2013)
- Biased Random-Key Genetic Algorithms: A Tutorial (21:57, 2 December 2013)
- The Discrete Event System Specification Formalism (19:59, 2 December 2013)
- Urban Operations Research (01:36, 2 December 2013)
- Stochastic Models for Design and Planning (01:34, 2 December 2013)
- Queueing Theory Books Online (01:31, 2 December 2013)
- Practical Queueing Theory in Java (01:31, 2 December 2013)
- Explore Queueing Theory for Scheduling, Resource Allocation and Traffic Flow Applications (01:28, 2 December 2013)
- Stochastic Processes Course Notes (01:26, 2 December 2013)
- Test Problems for Non-Linear Programming (01:23, 2 December 2013)
- OR Notes: Separable Programming (01:21, 2 December 2013)
- OR Notes: Non-Linear Programming (01:20, 2 December 2013)
Tags: decisao em grupo, decisão médica, otimização, previsão, problemas, programação em folha de cálculo, software de otimização, software estatístico
Useful Videos on Information Visualization
Posted by Armando Brito Mendes | Filed under estatística, videos, visualização
Bons videos sobre visualização de dados
Noah Iliinsky – Data Visualizations Done Wrong – A Beautiful Collection of Stories and Tips for Success.
The Four Pillars of Data Visualization
Designing Data Visualizations with Noah Iliinsky
Best Practices for Data Visualization
Designing Data Visualizatins
Seeing the Story in the Data and Learning to Effectively Communicate – Inspired by Stephen Few Principles, Visualization Guru
David McCandless: “The beauty of data visualization” – Data Detective Telling Stories From Visualization of Information
This also has a nice quiz about visualization principles.
As I collect more, I will consolidate this list.
Tags: belo, big data, data mining, image mining
17 short tutorials all data scientists should read
Posted by Armando Brito Mendes | Filed under estatística, materiais para profissionais
Excelentes textos fundamentais para cientistas dos dados
Here’s the list:
- Practical illustration of Map-Reduce (Hadoop-style), on real data
- A synthetic variance designed for Hadoop and big data
- Fast Combinatorial Feature Selection with New Definition of Predict…
- A little known component that should be part of most data science a…
- 11 Features any database, SQL or NoSQL, should have
- Clustering idea for very large datasets
- Hidden decision trees revisited
- Correlation and R-Squared for Big Data
- Marrying computer science, statistics and domain expertize
- New pattern to predict stock prices, multiplies return by factor 5
- What Map Reduce can’t do
- Excel for Big Data
- Fast clustering algorithms for massive datasets
- Source code for our Big Data keyword correlation API
- The curse of big data
- How to detect a pattern? Problem and solution
- Interesting Data Science Application: Steganography
Related link: The Data Science Toolkit
Tags: análise de dados, big data, captura de conhecimento, data mining, Excel, R-software
Little Book of R for Time Series!
Posted by Armando Brito Mendes | Filed under estatística, software
Um excelente tutorial sobre modelos de previsão simples no R
- How to install R
- Using R for Time Series Analysis
Tags: previsão, R-software
How many statisticians does it take to split a bill?
Posted by Armando Brito Mendes | Filed under estatística, software
stas
Bom blogue, bem disposto aborda diferenças entre estatística e ML
Some thoughts on the Fall term, now that Spring is well under way [edit: added a few more points]:
- RMarkdown and knitr are amazing. When I next teach a course using R, my students will be turning in homeworks using these tools: The output immediately shows whether the code runs and what its results are. This is much better than students copying and pasting possibly-broken code and unconnected output into a text file or (gasp) Word document.
- I’m glad my cohort socializes outside the office, taking each other out for birthday lunches or going to see a Pirates game. Some of the older PhD students are so focused on their thesis work that they don’t take time for a social break, and I’d like to avoid getting stuck in that rut.
However! Our lunches always lead us back to the age old question: How many statisticians does it take to split a bill? Answer: too long. I threw together a Shiny app, DinneR, to help us answer this question.
Tags: big data, data mining, R-software, software estatístico
Using Dates and Times in R
Posted by Armando Brito Mendes | Filed under estatística, software
Excelente sobre a utilização de tempos e datas no R
Today at the Davis R Users’ Group, Bonnie Dixon gave a tutorial on the various ways to handle dates and times in R. Bonnie provided this great script which walks through essential classes, functions, and packages. Here it is piped throughknitr::spin. The original R script can be found as a gist here.
Tags: data mining, R-software, software estatístico
The Dangers of Bling Data Visualizations
Posted by Armando Brito Mendes | Filed under estatística, visualização
Excelente de descrição de erros em visualização
The Dangers of Bling Data Visualizations
Given the volume of information that’s pouring into the enterprise from so many disparate sources, knowledge workers need to be able to visualize information in order to analyze it and extrapolate insights effectively.
When business users can visualize information, they’re able to process it more effectively and make faster and better decisions, according to Aberdeen research. Business users are constantly seeking the best ways to understand the data behind the data. If a monthly sales figure is low, what are the reasons the sales team is underperforming? The most effective way to help business users understand the data behind the data is by making it visual for them.
Data visualization has recently made its way into the mainstream by the way of infographics, business intelligence dashboards and, in some cases, statistical graphics. However, today data visualization comes in many forms and more often than not there might be too much “bling” incorporated into these data representations, leaving an audience with nothing more than a pretty picture. In this article, we contrast some good and bad examples of visualizations via examination of the salient features of the graphical displays. We will also demonstrate how poorly designed visualizations can lead to erroneous decisions.
Tags: big data, data mining, Estat Descritiva
