# Welcome

## My Quotes in Statistics: Sunday, Dec. 30

53 Kuotes | 50 Books## Import Kindle clippings easily

Beta status: Bulk Kuote import!!!!### Log in & Sign in using:

### Statistics: Sunday, Dec. 30

InstapaperHome statistics.com ? Archive ? Like & ArchiveStatistics: Sunday, Dec. 30 -

*Instapaper*

For examples of other applications, see the special issue of Proc. ACM 38(3), 1995, and the Microsoft Decision Theory GroupStatistics: Sunday, Dec. 30 -

*Instapaper*

The most widely used Bayes Nets are undoubtedly the ones embedded in Microsoft?s products, including the Answer Wizard of Office 95, the Office Assistant (the bouncy paperclip guy) of Office 97, and over 30 Technical Support Troubleshooters.Statistics: Sunday, Dec. 30 -

*Instapaper*

Archive All ? Download NewestStatistics: Sunday, Dec. 30 -

*Instapaper*

The standard deviation formula is essentially the same as the pythagorean formula. The pythagorean formula, if you remember from geometry, establishes the length of the hypotenuse of a right triangle. Working backwards, if you know the hypotenuse, you can figure out the length of each leg. The pyathogorean formula thus allows you to standardize different right triangles (ie, giving one number to use for comparison), and to describe multiple properties of each one (ie, two legs). Its properties carry over to any measurement of distance, and is commonly used whenever distance is being measured. Standard deviation is essentially a standardized, easily comparable measurement of distance.Statistics: Sunday, Dec. 30 -

*Instapaper*

Statistics: Standard Deviation khanacademy.orgStatistics: Sunday, Dec. 30 -

*Instapaper*

Statistics: Alternate Variance Formulas khanacademy.orgStatistics: Sunday, Dec. 30 -

*Instapaper*

Statistics en.wikibooks.orgStatistics: Sunday, Dec. 30 -

*Instapaper*

openanalytics.eu ? Archive ? Like & Archive ? Like R Service Bus Having the right algorithm is a first big step to get advanced analytics solve your problem and inform your decisions. The next one is to have the algorithm work for you and integrate it in your workflows and business processes. The R Service Bus is a swiss army knife that allows you to plug R into your processes independently of the technology used by other software applications involved in the workflow.Statistics: Sunday, Dec. 30 -

*Instapaper*

stackd/gauss github.com ? Archive ? Like & ArchiveStatistics: Sunday, Dec. 30 -

*Instapaper*

Gauss JavaScript statistics and analytics library - Node.JS ready Evented, asynchronous, and fast, Node.JS is an attractive platform for data mining, statistics, and data analysis. Gauss makes it easy to calculate and explore data through JavaScript.Statistics: Sunday, Dec. 30 -

*Instapaper*

What is a statistical model? A statistical model is a mathematical model which is modified or trained by the input of data points. Statistical models are often but not always probabilistic. Where the distinction is important we will be careful not to just say ?statistical? but to use the following component terms: A mathematical model specifies a relation among variables, either in functional form that maps inputs to outputs (e.g. y = m x + b) or in relation form (e.g. the following (x, y) pairs are part of the relation). A probabilistic model specifies a probability distribution over possible values of random variables, e.g., P(x, y), rather than a strict deterministic relationship, e.g., y = f(x). A trained model uses some training/learning algorithm to take as input a collection of possible models and a collection of data points (e.g. (x, y) pairs) and select the best model. Often this is in the form of choosing the values of parameters (such as m and b above) through a process of statistical inference. Claude ShannonStatistics: Sunday, Dec. 30 -

*Instapaper*

On Chomsky and the Two Cultures of Statistical Learning norvig.com ? Archive ? Like & ArchiveStatistics: Sunday, Dec. 30 -

*Instapaper*

First the data modeling culture (to which, Breiman estimates, 98% of statisticians subscribe) holds that nature can be described as a black box that has a relatively simple underlying model which maps from input variables to output variables (with perhaps some random noise thrown in). It is the job of the statistician to wisely choose an underlying model that reflects the reality of nature, and then use statistical data to estimate the parameters of the model. Second the algorithmic modeling culture (subscribed to by 2% of statisticians and many researchers in biology, artificial intelligence, and other fields that deal with complex phenomena), which holds that nature?s black box cannot necessarily be described by a simple model. Complex algorithmic approaches (such as support vector machines or boosted decision trees or deep belief networks) are used to estimate the function that maps from input to output variables, but we have no expectation that the form of the function that emerges from this complex algorithm reflects the true underlying nature.Statistics: Sunday, Dec. 30 -

*Instapaper*

MIT OpenCourseWare - Mathematics - 18.443 Statistics for Applications,Statistics: Sunday, Dec. 30 -

*Instapaper*

A map of the Tricki | Tricki tricki.org ? Archive ? Like & ArchiveStatistics: Sunday, Dec. 30 -

*Instapaper*

Khan Academy Probability and Statistics Online Statistics Education: An Interactive Multimedia Course of Study http://onlinestatbook.com/ CMU Open Learning Initiative Statistics Introduction to Statistical Thought BookStatistics: Sunday, Dec. 30 -

*Instapaper*

Conditional independence in Bayes Nets In general, the conditional independence relationships encoded by a Bayes Net are best be explained by means of the ?Bayes Ball? algorithm (due to Ross Shachter), which is as follows:Statistics: Sunday, Dec. 30 -

*Instapaper*

One very interesting question is: can we distinguish causation from mere correlation? The answer is ?sometimes?, but you need to measure the relationships between at least three variables; the intution is that one of the variables acts as a ?virtual control? for the relationship between the other two, so we don?t always need to do experiments to infer causality. See the following books for details. ?Causality: Models, Reasoning and Inference?, Judea Pearl, 2000, Cambridge University Press. ?Causation, Prediction and Search?, Spirtes, Glymour and Scheines, 2001 (2nd edition), MIT Press. ?Cause and Correlation in Biology?, Bill Shipley, 2000, Cambridge University Press. ?Computation, Causation and Discovery?, Glymour and Cooper (eds), 1999, MIT Press.Statistics: Sunday, Dec. 30 -

*Instapaper*

## 's Books

Fedor Dostoiewski - Los Hermanos karamazov 34 Kuotes 100 erros de portugu?s frequentes no mundo corporativo | EXAME.com Camila Pati 45 Kuotes Wheat Belly William Davis, MD 219 Kuotes Orteg- ¦ón, Pacheco y Prieto - Marco l- ¦ógico Usuario 36 Kuotes Superviviente Chuck Palahniuk 35 Kuotes El Expediente. Una Historia Personal Garton Ash, Timothy 86 Kuotes Instapaper: Friday, Jun. 22 Instapaper 39 Kuotes Redalyc.La difícil articulación entre políticas universales y programas focalizados. Etnografía institucional del programa Bolsa Familia de Brasil Felipe Hevia de la Jara 34 Kuotes Panfleto antipedagógico Moreno Castillo, Ricardo 68 Kuotes User Centred Metrics for Web Apps Google Research 36299 34 Kuotes Dios Cristiano "Espíritu Santo" Juan Carlos Mesen 101 Kuotes Microsoft Word - GSocial Karen Mokate-JJS.doc miriamca 32 Kuotes KindleSEMOZ1 summa 105 Kuotes WIKI FUNDAMENTSL Desconocido 49 Kuotes CastroGomezSantiago-ElGiroDecolonial 33 Kuotes El Estado regresa al primer plano: estrategias de análisis en la investigación actual* pc 32 Kuotes Teaching in a Networked Classroom Savage, Jonathan 52 Kuotes The 33 Strategies Of War Greene, Robert 342 Kuotes Sexus Henry Miller 130 Kuotes CHISTES FRESCOS 2011 PERSONAL 50 Kuotes Big Data: A Revolution That Will Transform How We Live, Work, and Think Mayer-Schonberger, Viktor;Cukier, Kenneth 176 Kuotes La Cisma de Inglaterra Calderón 149 Kuotes AMARTYA SEN DESARROLLO Y LIBERTAD KV 116 Kuotes La protección social de cara al futuro: Acceso, financiamiento y solidaridad CEPAL 64 Kuotes The Signal and the Noise: The Art and Science of Prediction Silver, Nate 397 Kuotes Instapaper: Tuesday, Jun. 18 Instapaper 91 Kuotes KindleSEOMOZ2 summa 280 Kuotes Lombardi-D---EP m.petito@gmail.com 53 Kuotes bolivia_senda_lmad 76 Kuotes The 50th Law 50 Cent 148 Kuotes ¿Comer de nuestra tierra? Estudios de caso sobre tierra y producción de alimentos en Bolivia Fundación TIERRA 46 Kuotes Fifty Shades Darker James, E L 31 Kuotes Microsoft Word - piel_zapa.doc Gerson O. Suárez 87 Kuotes PB001 Diana 242 Kuotes WorthTesting1 es6.mike@gmail.com 31 Kuotes Capitulo_2_Usabilidad_v1_0 36 Kuotes La troika y los 40 ladrones Santiago Camacho 38 Kuotes FINANCIAMIENTO Y GESTIÓN DE LA EDUCACIÓN EN AMÉRICA LATINA Y EL CARIBE. SÍNTESIS CEPAL/UNESCO 48 Kuotes JOVENES MIGRACIÓN POTOSI - TESIS ALEMANA Katharina Jochem 114 Kuotes Jung-y-El-Tarot-Un-Viaje-Arquetipico sammy 386 Kuotes Protein Power: The High-Protein/Low-Carbohydrate Way to Lose Weight, Feel Fit, and Boost Your Health--In Just Weeks! Michael R. Eades; Mary Dan Eades 178 Kuotes Oszlak y Orellana - SADCI Oscar Oslak 36 Kuotes Aprendiendo A Quererse A Sí Mismo Walter Riso 77 Kuotes The Way of the Superior Man: A Spiritual Guide to Mastering the Challenges of Women, Work, and Sexual Desire David Deida 76 Kuotes Lasperas Juan 64 Kuotes Tema 5- Procesos de evangelización pastoral especial 157 Kuotes ttmik Ignacio 31 Kuotes Thinking with Flying Logic es6.mike@gmail.com 178 Kuotes Notícias Diárias Português 164 Kuotes Kindle4RSS - Aug 13 Kindle4rss 31 Kuotes