söndag 20 maj 2018

Jessica: Vitbok över vettlös folkräkning av främmande stam

DN.SE:

"Kåseri. Vad var verkligt vansinne enligt Statistiska Centralbyrån på 30-talet? Och vad är verkligt vettlöst att mäta då precis som nu? "

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Inom felmarginalen finns inga säkra förändringar

Foto: Pi Frisk / SvD / TT
Medierna | Sveriges Radio:

"Nyheter baserade på opinionsmätningar duggar tätt inför valet i höst. Nyheter om att ett parti backar, ett annat går framåt, eller att opinionen förändrats i en viss sakfråga. Men hur förhåller vi oss till felmarginalen?"

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lördag 19 maj 2018

Over 2000 years of economic history, in one chart

World Economic Forum:
"Long before the invention of modern day maps or gunpowder, the planet’s major powers were already duking it out for economic and geopolitical supremacy.

Today’s chart tells that story in the simplest terms possible. By showing the changing share of the global economy for each country from 1 AD until now, it compares economic productivity over a mind-boggling time period."

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Så görs en opinionsundersökning

Så görs en opinionsundersökning - DN.SE:



Två prestigefyllda priser till professor Lars Lyberg

Två prestigefyllda priser till professor Lars Lyberg - Statistiska Institutionen:

Professor Lars Lyberg har tilldelats två prestigefyllda priser 2013. Helen Dinerman Award "for career contributions to innovative research and to research methodology" och AAPOR Book Award.

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fredag 18 maj 2018

This Is America’s Hottest Job

Source:mac905/Stockphoto
This Is America’s Hottest Job - Bloomberg:
"Murray Webb had been a lackluster student more interested in sports than schoolwork while attending a small Virginia college. Then he transferred to Kennesaw State University in suburban Atlanta to pursue a master’s degree in applied statistics and landed four job offers upon graduation. Webb, 33, now earns $160,000 a year targeting health-care customers for hospitals and says he is approached weekly by companies and recruiters seeking data scientists."

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torsdag 17 maj 2018

Easily prepare data for analysis with Google Cloud

(61) Easily prepare data for analysis with Google Cloud (Google Cloud Next '17) - YouTube:



80% of data analysts and scientists time is spent in data preparation, including finding, cleaning and organizing data, and this is also the least favorite part of their job (according to Forbes). Accelerating the data preparation process will help you to gain insights from the data faster. Watch this video to understand the best practices and explore tools for preparing data quickly and easily.

lördag 12 maj 2018

Florence Nightingale (1820–1910)

Amstat News: Born on this day in 1820: #statistician Florence Nightingale, #dataviz pioneer.
"In 1840, Florence Nightingale begged her parents “to let her study mathematics instead of doing worsted work and practicing quadrilles.” Her mother “did not approve, home duties were not to be neglected for mathematics.” She assumed that her daughter’s destiny was marriage, “and what use were mathematics to a married woman?” Her father, who loved math and had communicated that love to his daughter, nevertheless urged her to study more appropriate subjects (for a woman), “history or philosophy, natural or moral.” Florence expressed her preference for mathematics by saying, “I don’t think I shall succeed so well in anything that requires quickness as in what requires only work.” [1] Her parents finally granted permission. Years later, her mathematical approach saved the British army at Scutari during the Crimean war and provided the data that led to hospital reforms. [2]"

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Leveraging AI in the public sector with open data

Europeiska Data Portalen:

"Using AI in the public sector is possible, but how?

Artificial Intelligence (AI) software has been called the most disruptive force in technology and it offers an unprecedented opportunity to transform both the private- and public services sector. It is a priority for the European Union and the European Commission recently presented a series of measure to boost Europe’s competitiveness in this field. In the public sector, AI applications are still only used to a small extent though. A key question is: how can the potential of AI applications in the public sector be unleashed? Open Data can play an important role in realizing this.

 What can AI do for society?

AI techniques can unravel deeper insights from sets of data than traditional statistical techniques. Examples of AI are: speech recognition, natural language processing, chatbots or voice bots. In most cases, AI applications have at least one of the following seven functions: monitoring, discovering, predicting, interpreting, interacting with the physical environment, interacting with humans and interacting with machines."

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söndag 29 april 2018

3 things you can’t do with math

Image Credit: Zapp2Photo/Shutterstock
3 things you can’t do with math | VentureBeat:
"I’ve been doing analytics, data science and statistics for a long time, and I remember when analytics was just called “math.” I walked around the RSA Conference show floor this year, and I would like to apologize on behalf of the entire analytics industry for all the noise out there on the subject. There’s no doubt that AI and analytics are revolutionizing many industries — especially the cybersecurity industry. But it’s not a silver bullet, because there are limitations to what math can actually accomplish. Let’s look at three, in the hopes that it will help you navigate the noise."

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lördag 28 april 2018

New Decimal Systems - Great Sandbox for Data Scientists and Mathematicians

Data Science Central:
"We illustrate pattern recognition techniques applied to an interesting mathematical problem: The representation of a number in non-conventional systems, generalizing the familiar base-2 or base-10 systems. The emphasis is on data science rather than mathematical theory, and the style is that of a tutorial, requiring minimum knowledge in mathematics or statistics. However, some off-the-beaten-path, state-of-the-art number theory research is discussed here, in a way that is accessible to college students after a first course in statistics. This article is also peppered with mathematical and statistical oddities, for instance the fact that there are units of information smaller than the bit.

You will also learn how the discovery process works, as I have included research that I thought would lead me to interesting results, but did not. In all scientific research, only final, successful results are presented, while actually most of the research leads to dead-ends, and is not made available to the reader. Here is your chance to discover these hidden steps, and my thought process!"

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onsdag 25 april 2018

Statistics and Big Data: A fast track to success

Statistics and Big Data: A fast track to success - Study International:

“Statistics is the grammar of science.” – Karl Pearson

"The global explosion of computerised statistics has given life to the Big Data Revolution. With the amount of data produced in the past few years alone far exceeding any human data previously recorded, it’s fair to say that statistics and Big Data are a BIG deal.

In the age of the Internet, it becomes critically essential for businesses and corporations in virtually every sector to harness data that can be used for analysis and discovery. Regardless of whether your profession lies in healthcare, communications, bandwidth or something more complex, the power of numbers and Big Data will allow you to make faster and smarter decisions."

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tisdag 24 april 2018

Hans Roslings regler för att förstå samtiden

Foto: Magnus Sandberg/IBL
Hans Roslings regler för att förstå samtiden | SvD:
"Hur lär man sig tänka som Hans Rosling? I en postumt publicerad bok presenteras vad den populäre professorn kallar "factfulness" – tio metoder för att se världen som den är, bortom såväl "fake news" som omedvetet förvrängda mediebilder."

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torsdag 19 april 2018

Dataskyddsförordningen


Statisticon bjuder in till diskussion… Hur får jag hantera personuppgifter?
Nu är det bara några veckor kvar tills Dataskyddsförordningen (GDPR) träder i kraft den 25 maj 2018. Skyddet för personuppgifter kommer därmed att stärkas. Och det här kommer att påverka allas vår vardag. Vad är egentligen personuppgifter? Och hur får vi behandla dem?

Advokat Lotta Wikman Öman från Ahlford Advokatbyrå ger en genomgång av GDPR och svarar på frågor samt ger råd avseende vilka åtgärder som behöver vidtas och rutiner som behöver tas fram för att kunna efterleva den kommande lagstiftningen.

…se mer på sajt www.snackastatistik.se

tisdag 10 april 2018

Martin Lagerström 2017 års statistikfrämjare

Martin Lagerström 2017 års statistikfrämjare | Statistikfrämjandet:

"I want to say big thank´s to the Swedish Statistical Society which has given me the award as “The Statistician of the Year!”

Video (3 min in Swedish) when I receive the prize:
https://dreambroker.com/channel/dfa01fqt/n0ztt5r7

Video (80 min in Swedish) when I present how to use fact-based approaches to innovate and thrive in business:
https://dreambroker.com/channel/dfa01fqt/iqvtbztq

The jury´s motivation for the Award: ”For innovative application of statistical methodology in the fields of business development and strategic competence development of managers and management teams”

Previous Winners of this Award is e.g. Prof. Hans Rosling"

måndag 9 april 2018

Non-tech businesses are beginning to use artificial intelligence at scale - GrAIt expectations

Economist - Non-tech businesses are beginning to use artificial intelligence at scale - GrAIt expectations:
"AI and machine learning (terms that are often used interchangeably) involve computers crunching vast quantities of data to find patterns and make predictions without being explicitly programmed to do so. Larger quantities of data, more sophisticated algorithms and sheer computing power have given AI greater force and capability. The outcomes are often similar to what an army of statisticians with unlimited time and resources might have come up with, but they are achieved far more quickly, cheaply and efficiently."

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onsdag 4 april 2018

Bill Gates Calls Factfulness One of the Most Important Books



Bill Gates Calls Factfulness One of the Most Important Books | Time:
Millions of people have tuned in for Swedish physician and statistician Hans Rosling’s TED Talks over the years, and the videos caught the attention of at least one famous fan: Bill Gates. Gates and his wife Melinda went on to befriend Rosling, who gained his global audience with insights on how data can help lead to better outcomes in global poverty and health.

tisdag 3 april 2018

Swansong of Hans Rosling, data visionary

Hans Rosling discusses population growth at the ReSource 2012 conference
in Oxford, UK.Credit: Matthew Lloyd/Getty Images for ReSource 2012
Nature - Swansong of Hans Rosling, data visionary:
Factfulness: Ten Reasons We’re Wrong About the World — and Why Things Are Better Than You Think Hans Rosling with Ola Rosling and Anna Rosling Rönnlund Flatiron: 2018.

Hans Rosling was many things. A physician and epidemiologist; a statistician and data visualizer; a staunch advocate of free data as the bedrock of an accurate world view. Factfulness is Rosling’s last, and posthumous, book; he died in February 2017. Like his other work, including his famous presentations, it throws down a gauntlet to doom-and-gloomers in global health by challenging preconceptions and misconceptions.

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lördag 17 februari 2018

Visst kan man lita på opinionsundersökningar

Medievärlden - Diskussion:
"Att VLT, och dess associerade publikationer, nu väljer att blankt vägra presentera opinionsundersökningar är ett uppseendeväckande ställningstagande, som på intet sätt bidrar till ett bättre undersökningsklimat, skriver branschorganisationen SMIF i ett svar till Daniel Nordström."

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tisdag 13 februari 2018

Häggström hävdar: Meningsutbyte med Bo Rothstein om matematisk modellering

Häggström hävdar:
"Bo Rothstein är med varje rimligt mått mätt en av Sveriges mest framstående statsvetare, och på tidningarnas debattsidor utgör han en frisk fläkt. Ibland går han dock en smula överstyr i sin argumentation, som i gårdagens artikel på DN Debatt, rubricerad Felaktig tolkning av metoo riskerar att skada tilliten. Det finns mycket att diskutera och kritisera i den artikeln, men här skall jag uppehålla mig vid en enda detalj, nämligen följande passage:
[På] min egen arbetsplats, Göteborgs universitet, [utförs] ett antal undersökningar [...] där de tillfrågade fått svara på frågan om de under det senaste året utsatts för sexuella trakasserier. Resultatet är att cirka 2 procent av kvinnorna uppger att de blivit utsatta (och ungefär 1 procent av männen).
Det är statistiskt inte helt enkelt att översätta dessa två procent per år till längre tidsperioder, men om man utgår från en anställningstid om 20 år är en någotsånär rimlig uppskattning att femton procent av de anställda kvinnorna blivit utsatta för vad de själva uppfattar vara sexuella trakasserier någon gång under en tjugoårsperiod.
Dessa 15% synes mig gripna ur luften, något som föranledde mig att igår skriva en Facebookuppdatering med följande innehåll."

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Så fungerar Tensorflow – verktygslådan för AI

TechWorld:
"Egentligen kan man lika gärna kalla maskininlärning för dataanalys, som för AI. Men eftersom tekniken gör helt nya analyslösningar möjliga är det naturligt att sortera in den under paraplybegreppet AI.

Ett sätt att beskriva maskininlärning är att det är en svart låda, i vilken man stoppar in data och får ut förutsägelser. Men hur gör man i praktiken för att bygga en lösning?"

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Så funkar maskininlärning – steg för steg

TechWorld:
"En allmän iakttagelse att är maskinlärning egentligen lika gärna kan kallas för dataanalys, eller till och med matte, som för AI. Att man kallar maskinlärning för AI kanske beror på att det är en teknik som gör det möjligt att dra slutsatser som människor åtminstone i de flesta fall inte klarar av."

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Why Data Analysis & Not Math Is A Prerequisite For Machine Learning

Why Data Analysis & Not Math Is A Prerequisite For Machine Learning
"If you are an absolute Machine Learning beginner and are wondering whether data analysis is a prerequisite, then here’s the hard-fact – data analysis meaning the task of gathering data, cleaning data, exploring and visualizing data is an absolute must before one gets started on machine learning."

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söndag 11 februari 2018

SCB: V-förslag inte förenligt med lagen

Sydsvenskan:
"Vänsterpartiet vill att SCB ska börja föra statistik över etnicitet och religion – men den berörda myndigheten avfärdar idén. – Det är inte tillåtet att samla in statistik över etnisk tillhörighet, säger Nizar Chakkour, pressansvarig på SCB."

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Why is it so hard to train data scientists?

Data Science Central:
"A data scientist must also be highly familiar with statistics, and understand multiple statistical methods for tasks such as regression, dimensionality reduction, statistical significance analysis, Mote Carlo simulations, and Bayesian methods, to name a few. The data scientist needs to have knowledge in statistics at a level close to the knowledge of the statistician."

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fredag 26 januari 2018

Great R packages for data import, wrangling and visualization


Computerworld:
Here are my go-to R packages -- in a handy searchable table.
One of the great things about R is the thousands of packages users have written to solve specific problems in various disciplines -- analyzing everything from weather or financial data to the human genome -- not to mention analyzing computer security-breach data.
[ Need to learn R or brush up on basics? Download our free Beginner's Guide to R or the Advanced Beginner's Guide to R ]Some tasks are common to almost all users, though, regardless of subject area: data import, data wrangling and data visualization. The table below show my favorite go-to packages for one of these three tasks (plus a few miscellaneous ones tossed in). The package names in the table are clickable if you want more information. To find out more about a package once you've installed it, type help(package = "packagename") in your R console (of course substituting the actual package name ).
[To comment on this story, visit Computerworld's Facebook page.]
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måndag 22 januari 2018

7 Visualizations You Should Learn in R

Data Science Central:
With ever increasing volume of data, it is impossible to tell stories without visualizations. Data visualization is an art of how to turn numbers into useful knowledge.

R Programming lets you learn this art by offering a set of inbuilt functions and libraries to build visualizations and present data. Before the technical implementations of the visualization, let’s see first how to select the right chart type.

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Factfulness: Ten Reasons We're Wrong About the World--and Why Things Are Better Than You Think

Hans Rosling, Anna Rosling Rönnlund, Ola Rosling: 9781250107817: Amazon.com: Books
Factfulness: The stress-reducing habit of only carrying opinions for which you have strong supporting facts.

When asked simple questions about global trends―what percentage of the world’s population live in poverty; why the world’s population is increasing; how many girls finish school―we systematically get the answers wrong. So wrong that a chimpanzee choosing answers at random will consistently outguess teachers, journalists, Nobel laureates, and investment bankers.

In Factfulness, Professor of International Health and global TED phenomenon Hans Rosling, together with his two long-time collaborators, Anna and Ola, offers a radical new explanation of why this happens.