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

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"

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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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.

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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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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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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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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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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Omdiskuterad kursbok i statistik

https://www.svtplay.se/video/16723397/sverige-idag/sverige-idag-24-jan-17-30-1?start=auto

Sverige idag - Idag 17.30 | SVT Play: 12,5 minuter in i programmet

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.

Read more....

Selected Recent Articles from Top DSC Contributors

This is a new series, featuring great content from our top contributors. Some of these articles are rather technical in nature, but many are business-oriented and written in simple English. The entire series consists of about 120 articles. We intend to publish a new set every two weeks or so. Click here to check out the previous edition. To read more articles from a same author, read one of his/her articles and click on his/her profile picture to access the full list. Some of these articles are curated or posted as guest blogs.

Selected Recent Articles from Top DSC Contributors

EMOS WEBINARS 2018

EMOS WEBINARS 2018:
Registrations for the next three EMOS Webinars are now open. Registration is on a first-come first-serve basis.

Webinar title: Web surveys
Presenters: Vasja Vehovar and Nejc Berzelak, University of Ljubljana
Date: 7 February 2018

Webinar title: Innovations in business statistics data collection
Presenter: Ger Snijkers, Statistics Netherlands
Date: 21 February 2018

Webinar title: Statistical monitoring of sustainable development at global, EU and national level (with a case study of Poland)
Presenters: Nicola Massarelli, Eurostat, and Monika Gorzelak, Statistics Poland
Date: 28 February 2018

You can check the content and register for these webinars at: http://konference.ef.uni-lj.si/emos/webinars/ where you will also find the recording of the webinar The European Statistical System that took place on 10 January 2018.

The Guinness Brewer Who Revolutionized Statistics

The Guinness Brewer Who Revolutionized Statistics:
One of the greatest minds in 20th Century statistics was not a scholar. He brewed beer.

Guinness brewer William S. Gosset’s work is responsible for inspiring the concept of statistical significance, industrial quality control, efficient design of experiments and, not least of all, consistently great tasting beer.

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Traits of a Successful Statistician

Traits of a Successful Statistician:
It goes without saying that a successful statistician must have strong analytical and technical skills. Clearly, you need to know and understand statistics—this is, after all, the added value that you uniquely provide. Most statisticians have master’s degrees, but some—especially those who plan to go into academia—earn PhDs. Still others might hold, at least initially, an undergraduate degree only. How far to take your training is highly dependent on the specific career path you expect to follow.

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