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Statistical Tables. History of Statistics. Peter M.

History of Statistics

Lee, 24 August 1940 — 10 March 2017. Introduction to Probability. Data Science Association. Data Science Association. Causal Analysis in Theory and Practice » Data versus Science: Contesting the Soul of Data-Science. Playlists. Libros que consultar para comenzar a formarte en el mundo del Big Data. Este es un campo muy complejo, y produce gran rechazo a las personas que tienen un conocimiento escaso de él o escuchan por primera vez la palabra Big Data.

Libros que consultar para comenzar a formarte en el mundo del Big Data

SQL

El matemático y youtuber que enseña (con comedia) la materia más odiada. Eduardo Sáenz de Cabezón es doctor en matemáticas, pero también es cuentacuentos y hace monólogos de comedia para divulgar la ciencia que más le apasiona.

El matemático y youtuber que enseña (con comedia) la materia más odiada

El investigador de la Universidad de la Rioja (España) –y ahora también youtuber– saltó a la fama gracias a una charla de TED Talk donde hace reír a un auditorio repleto hablando de una de las materias más odiadas en la escuela. “Cuando alguien te pregunta para qué sirven las matemáticas, no te está preguntando por aplicaciones de las ciencias matemáticas. Te está preguntando ‘Y yo por qué tuve que estudiar esa mierda que no volví a usar nunca?”

, dice Sáenz al comienzo de esa conferencia que acumula más de 1.7 millones de visualizaciones. Foundations of Data Science Textbook.

Python

R Stat. STATISTICS. Databases. Coding. Maps and Viz. Bibliography. Examples. Class Material. Lectures: You can obtain all the lecture slides at any point by cloning 2015, and using git pull as the weeks go on.

Class Material

Videos: You can see the entire list of videos here. Below we list them by class/section along with a link to the slides. We’ve also started a YouTube channel for cs109. This channel has smaller videos dealing with nitty gritty stuff on the course. Labs/Sections: Note that the Lab video and notebook is actually recorded and produced on the Thursday and Friday of the previous week, but is listed under the week that sections pertaining to the material on the Lab are given. OpenIntro. Analysis of Variance (ANOVA) Using Data to Find the Angriest Death Grips Song. Excel Total - Expertos en Excel. Beware of Zombie Statistics … Even When It’s Not Halloween. (October 2017) Do women really own less than 2 percent of the world’s land?

Beware of Zombie Statistics … Even When It’s Not Halloween

Do women constitute 70 percent of the world’s poor? Do women provide between 60 percent and 80 percent of the agricultural labor in Africa? Top 52 Free Statistical Software - Editor Review, User Reviews, Features, Pricing and Comparison in 2017 -Predictive Analytics Today. 687694. Majority to minority: the declining U.S. white population]Quand la majorité devient minorité : le cas des blancs aux Etats-Unis. In this essay we document the demography of the decline of the white population in the United States, a country with a long history of white supremacy.

Majority to minority: the declining U.S. white population]Quand la majorité devient minorité : le cas des blancs aux Etats-Unis

Despite the fact that the U.S. Constitution and the civil rights legislation of the 1960s guaranteed equality to all people irrespective of race or ethnicity, everyone is far from equal in the United States today. On average, whites are far better off economically and educationally and in many other ways than are minority peoples. Levels of residential segregation by race and ethnicity are still nearly as high as they were decades ago. Yet, the share of the U.S. population that is white has declined over the past six decades from about 90 percent in 1950 to 61 percent in 2016 (table 1) and will likely drop below 50 percent in another 30 years: what once was a majority will become a minority relatively soon, and has already become so in a few states.

First immigrants to the U.S. Whites and minorities in the U.S. Handy statistical lexicon. These are all important methods and concepts related to statistics that are not as well known as they should be.

Handy statistical lexicon

I hope that by giving them names, we will make the ideas more accessible to people: Mister P: Multilevel regression and poststratification. 40 Techniques Used by Data Scientists. These techniques cover most of what data scientists and related practitioners are using in their daily activities, whether they use solutions offered by a vendor, or whether they design proprietary tools.

40 Techniques Used by Data Scientists

When you click on any of the 40 links below, you will find a selection of articles related to the entry in question. Asdfree. Learn Data Science: Tutorials, Online Courses, Books, & More. Toward sustainable insights, or why polygamy is bad for you. Summer Olympics: Legends - Microsoft Power BI Community. Las consecuencias de no renovar el censo durante más de una década en Colombia. Free Statistics Book. Big Data, Data Mining, Predictive Analytics, Statistics, StatSoft Electronic Textbook. This free ebook has been provided as a public service since 1995.

Big Data, Data Mining, Predictive Analytics, Statistics, StatSoft Electronic Textbook

Statistics: Methods and Applications textbook offers training in the understanding and application of statistics and data mining. It covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics, credit scoring, forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others. Mathematicians mapped out every “Game of Thrones” relationship to find the main character — Quartz. Fans of the Game of Thrones books and TV series have long quarreled over who the true hero of the story is.

Mathematicians mapped out every “Game of Thrones” relationship to find the main character — Quartz

Daenerys? Tyrion? Jon Snow? Hodor? Every time a character seems to be developing into a protagonist, he or she is brutally killed (video). But several main characters remain. Math 101: A reading list for lifelong learners. Ready to level up your working knowledge of math? Here’s what to read now — and next. Math 101, with Jennifer Ouellette First, start with these 5 books… 1. A Lesson in the Errors of Statistical Thinking: Nate Silver on Trump. Alyssa frazee. Thu 02 January 2014 | -- (permalink) [1505.04714] Alan M. Turing: The Applications of Probability to Cryptography. Photomath. Mathpix! Introduction to Metadata. Metadata is organised information that describes, locates or otherwise makes it easier to retrieve information. Metadata is all around us, it started as catalogue cards in libraries and is now used mainly in a digital manner.

Metadata is everywhere, every webpage, every file, picture, piece of software has metadata that describes what it is, when was it created, what size it is, generally everything you or a computer needs to know to efficiently find information. There are two main types of metadata, descriptive and structural. Descriptive metadata is information that is used for identification or discovery of a resource. It can be a title, abstract, author or keywords. Metadata provides important benefits to a business including: Consistency – metadata has information that helps business users understand the difference between business terms such as: clients and consumers, revenue and sales and so on. Top 50 Free Statistical Software. How I Acted Like A Pundit And Screwed Up On Donald Trump.

Since Donald Trump effectively wrapped up the Republican nomination this month, I’ve seen a lot of critical self-assessments from empirically minded journalists — FiveThirtyEight included, twice over — about what they got wrong on Trump. This instinct to be accountable for one’s predictions is good since the conceit of “data journalism,” at least as I see it, is to apply the scientific method to the news. That means observing the world, formulating hypotheses about it, and making those hypotheses falsifiable. Best Data Science Online Courses. The number of online data science courses have exploded in recent years and there courses for any needs. Here is a extensive list of free and paid courses from Coursera, DataCamp, Dataquest, edX, Udacity, Udemy, and other major providers.

By Brendan Martin, (LearnDataSci). The following is a comprehensive list of Data Science courses and resources that explain or teach skills within Data Science, such as machine learning, data mining, analytics, cleaning, visualization, scraping, using APIs to make data products, artificial intelligence, and much more. Dr. Wolfgang Rolke Home Page. Database System Rankings 2016. Introduction to Data Quality. Data Science - Part II - Working with R & R Studio. The Season for Sharing Data: Working with the newly released Census 2010-2014 ACS 5 year data in R. On December 3, 2015 the U.S. Census Bureau released the 2010-2014 5 year ACS (American Community Survey) data.

You can read all about it on the Census website. This fantastic five-year statistical database provides aggregate social and economic characteristics about American individuals and families down to the block group level. 20 Big Data Repositories You Should Check Out.

Coursera- R Programming

Coursera-Data Toolbox. Weka 3 - Data Mining with Open Source Machine Learning Software in Java. Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Mass Shooting Tracker. RepASA. Deducer: A GUI for R - Deducer Manual. LeaRning Path on R - Step by Step Guide to Learn Data Science on R. AFAMaC-Matemáticas. Gun Violence Archive. HyperStat Online: An Introductory Statistics Textbook and Discussion of whether most published research is false. Recommend HyperStat to your friends on Facebook Click here for more cartoons by Ben Shabad.

Griffith Feeney Consulting. Introduction to Data Science with R - O’Reilly Media. Jtleek/datasharing. DARPA - Open Catalog. StatsLife - Significance back issues. Spurious Correlations. ISLP — Poster Competition 2014-2015. National Statistical Service § Sample Size Calculator. Tiimgreen/github-cheat-sheet. Computing for Social Sciences, Winter 2015.