torsdag 13 december 2018

The Role of Theory in Data Analysis

Simply Statistics:
In data analysis, we make use of a lot of theory, whether we like to admit it or not. In a traditional statistical training, things like the central limit theorem and the law of large numbers (and their many variations) are deeply baked into our heads. I probably use the central limit theorem everyday in my work, sometimes for the better, and sometimes for the worse. Even if I’m not directly applying a Normal approximation, knowledge of the central limit theorem will often guide my thinking and help me to decide what to do in a given data analytic situation.

tisdag 11 december 2018

Industrialisation & professionalisation of Data Science


https://youtu.be/I9jXnLGUvNU
The RSS Data Science Section presents the results from a series of regional workshops held during 2018 on the “Industrialisation and professionalization of Data Science”. 

The findings will relate to 4 questions of the 12 noted at the DSS launch event and include: 
- What does a good DS workflow look like? 
- How should DS fit into the structure of an organisation 
- What do executives and managers need to know about DS 
- What is a Data Scientist’s responsibility to wider society? 

måndag 10 december 2018

What Great Data Analysts Do — and Why Every Organization Needs Them

VICKI JAURON, BABYLON AND BEYOND
PHOTOGRAPHY/GETTY IMAGES
Harvard Business Review:

The top trophy hire in data science is elusive, and it’s no surprise: a “full-stack” data scientist has mastery of machine learning, statistics, and analytics. When teams can’t get their hands on a three-in-one polymath, they set their sights on luring the most impressive prize among the single-origin specialists. Which of those skills gets the pedestal?

Read more...

tisdag 4 december 2018

Bootstrapping an International Prize

Stats and Stories Episode 72 — Stats + Stories

Brad Efron is Max H. Stein Professor of Humanities and Sciences and Professor of Statistics at Stanford University, and Professor of Biostatistics with the Department of Biomedical Data Science in the Stanford School of Medicine; he serves as Co-director of the undergraduate Mathematical and Computational Sciences Program administered by the Department of Statistics. He has held visiting faculty appointments at Harvard, UC Berkeley, and Imperial College, London. He has been recognized with the 2018 International Prize in Statistics.

Five projects that are harnessing big data for good

måndag 3 december 2018

Cathie Marsh memorial lecture - Is there a future for surveys?


https://youtu.be/Zb1hFc6MqPo

Speakers: 
- Guy Goodwin, Chief Executive of National Centre for Social Research 
- Tom Smith, Managing Director of the Data Science campus at ONS 

söndag 2 december 2018

Vem vill du uppmärksamma i Statistikvärlden?

Statistikfrämjandet:
Senast lördagen den 15 december är det dags att skicka in nomineringar till Årets Statistikfrämjare!

Detta pris delas ut årligen i samband med Statistikfrämjandets årsmöte, och tilldelas:
”En eller flera personer, verksamma i eller anknutna till Sverige, som gjort en slagkraftig insats på statistikområdet som under det senaste året givet publik uppmärksamhet. Insatsen kan bestå av en innovativ metod, en smart analys eller på ett framgångsrikt sätt ha utmanat en etablerad sanning."

Ta chansen att nominera någon som DU tycker gjort något riktigt slagkraftigt för statistikvärlden! Skicka ditt bidrag till Stig-Johan Wiklund på sj@idevator.se senast den 15 december 2018.

Utdelningen av priset kommer att äga rum vid Statistikfrämjandets årsmöte i Göteborg den 21-22 mars 2019.

Välkommen med nomineringar!

Responsive and Adaptive Design for Survey Optimization

Journal of Official Statistics
We discuss an evidence-based approach to guiding real-time design decisions during the course of survey data collection. We call it responsive and adaptive design (RAD), a scientific framework driven by cost-quality tradeoff analysis and optimization that enables the most efficient production of high-quality data. The notion of RAD is not new; nor is it a silver bullet to resolve all the difficulties of complex survey design and challenges. RAD embraces precedents and variants of responsive design and adaptive design that survey designers and researchers have practiced over decades. In this paper, we present the four pillars of RAD: survey process data and auxiliary information, design features and interventions, explicit quality and cost metrics, and a quality-cost optimization tailored to survey strata. We discuss how these building blocks of RAD are addressed by articles published in the 2017 JOS special issue and this special section. It is a tale of the three perspectives filling in each other. We carry over each of these three perspectives to articulate the remaining challenges and opportunities for the advancement of RAD. We recommend several RAD ideas for future research, including survey-assisted population modeling, rigorous optimization strategies, and total survey cost modeling.

Read more...

Dare to Compare – part 3

Stats With Cats Blog

Parts 1 and 2 of Dare to Compare summarized fundamental topics about simple statistical comparisons. Part 3 shows how those concepts play a role in conducting statistical tests. The importance of these concept are highlighted in the following table.

Read more...

lördag 1 december 2018

How to get a job working with artificial intelligence/machine learning

The Next Web: How to get a job working with artificial intelligence/machine learning
Artificial intelligence is one of the most exciting and attractive fields to get into. The global machine learning (ML) market is estimated to grow from $1.4 billion in 2017 to $8.8 billion by 2022. AI is projected to create 2.3 million related jobs by 2020, according to Gartner. The average salary of a machine learning engineer is between $125,000 and $175,000. At the top ten highest paying companies for AI talent, the average salary easily surpasses $200,000. Clearly, there are a lot of reasons to join this booming industry.

Read more...

fredag 30 november 2018

New methods and sources for Big Data research

© Marcel van Hoorn
Statistics Netherlands: New methods and sources for Big Data research
In October 2018, the seminar ‘Methods for Big Data in Official Statistics’ was held on the Brightlands Smart Services Campus in Heerlen. The objective of the seminar was to bring together researchers from statistical offices and academic scientists in order to exchange knowledge and present the latest methods and techniques in the field of Big Data. In addition, experiences were shared in terms of the use of new data sources and the associated methodological challenges. The seminar was organised by Statistics Netherlands (CBS).

Shaping the Future of Technology Through Data Science and Statistics


Analytics Insight: Cornell University
Cornell University was founded in 1865 in Ithaca, New York by Andrew D. White and Ezra Cornell, the latter famously stating “I would found an institution where any person can find instruction in any study.” The founders could not have envisioned the full extent of modern data science, of course, but scientific research of all types has been at the heart of Cornell’s mission since its beginning. Statistics itself – the precursor or original discipline underlying data science – first came to prominence at Cornell after World War II, with the presence of two seminal figures in the field, Jack Kiefer and Jacob Wolfowitz, as faculty members. Since then, Cornell’s Department of Statistics and Data Science (as it is now called) has hosted and continues to be the home of many prominent researchers in theoretical and applied statistical methods.

onsdag 28 november 2018

Frimis-seminar

Läs mer om seminariet..... 

tisdag 27 november 2018

Royal Statistical Society Awards Ceremony


https://youtu.be/-64NsXCW0V4

Winners: - 00:11 Guy medal in Silver: Peter Buhlman, ETH Zurich - 03:42 Guy medal in Bronze: Peng Ding, University of California, Berkeley - 06:48 Barnett Award: Peter Diggle, Lancaster University and Health Data Research UK - 11:42 Research Prize: Emanuele Giorgi, Lancaster University - 14:32 West Medal: Jill Leyland, Consultant - 18:53 Greenfield Industrial Medal: Idris Eckley, Lancaster University - 22:15 Bradford Hill Medal: Nicky Best, Imperial college London - 23:15 Howard Medal: Colin Aitken, The University of Edinburgh - 26:27 Mardia Prize: Water Research Institute - Cardiff University

Statistikfrämjandet - Nyhetsbrev november 2018


måndag 26 november 2018

What is the bootstrap?

Significance magazine

Bradley Efron (pictured) was awarded the 2018 International Prize in Statistics for the creation of the “bootstrap”, a method that “transformed science’s ability to use and understand data and helped usher in the era of data analysis through computing”. But what is the bootstrap? James J. Cochran explains.

Read more.... and about the Prize

fredag 23 november 2018

Debatt i Lund - AI: Hur smart är konstgjord intelligens?


https://youtu.be/FzQgM3wAMag

Från Häggström hävdar: Videofilmad i lärdomsstaden

Gårdagens Debatt i Lund (som jag annonserade i mina två föregående bloggposter) med Andreas Ekström (moderator), Anna Felländer, Thore Husfeldt, Alfred Ruthoch mig på temat "Hur smart är konstgjord intelligens?" videofilmades och kan ses nedan. Det timslånga samtalet kretsade kring den artificiella intelligensens framtid, och blev bitvis intressant, men jag känner (liksom gissningsvis två av de andra panelisterna) att jag gott kunde ha tagit för mig lite mer. Kanske nästa gång - i Stockholm på torsdag.

torsdag 22 november 2018

AI peer reviewers unleashed to ease publishing grind

Nature:
A suite of automated tools is now available to assist with peer review but humans are still in the driver's seat.
Automated tools could help take the slog out of peer review.
Credit: Mary Evans/Classicstock/H. Armstrong Roberts

Most researchers have good reason to grumble about peer review: it is time-consuming and error-prone, and the workload is unevenly spread, with just 20% of scientists taking on most reviews.

Now peer review by artificial intelligence (AI) is promising to improve the process, boost the quality of published papers — and save reviewers time.

A handful of academic publishers are piloting AI tools to do anything from selecting reviewers to checking statistics and summarizing a paper’s findings.

onsdag 21 november 2018

Misunderstanding the global burden of alcohol

Qvintensen webbtidskrift
Harmful alcohol consumption is known to cause several diseases and many deaths. A study published in the Lancet this August has presented the latest figures, pertaining to the year 2016. The authors estimate that alcohol answers for approximately 7% of all male and 2% of all female deaths, as well as 6% of male and 2% of female disability-adjusted life year losses. Moreover, respective estimates were presented for all countries over several years. But these estimates seem to be too high.

tisdag 20 november 2018

John Pullinger - Statistics making an impact


https://youtu.be/0-naaUqfWO0

RoyalStatSoc
John Pullinger, National Statistician, gives a historical perspective on statistical systems from around the world and how they have interacted with democracy and society; what does the state need to put in place to allow independent statistics to inform better decisions?

måndag 19 november 2018

In defence of Statistics Canada's request for financial data

Canadians are up in arms about Statistics Canada’s push for
their financial data. They shouldn’t be. (Shutterstock)
Qvintensen Webb
Statistics Canada’s proposal to collect a range of detailed financial data from 500,000 Canadians has certainly touched a nerve.

Many commentators argue this invades privacy and is overreach, while only a few brave pundits defend the plan. The tide of public opinion has turned and our system of official statistics is under serious threat.

Three questions need answering.

söndag 18 november 2018

What is machine learning? We drew you another flowchart

It pretty much runs the world.

MIT Technology Review

The vast majority of the AI advancements and applications you hear about refer to a category of algorithms known as machine learning. (For more background on AI, check out our first flowchart here.)

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you. If it can be digitally stored, it can be fed into a machine-learning algorithm.

tisdag 13 november 2018

Mastering Machine Learning

MathWorksStep-by-Step Guide with MATLAB
Ready to start applying machine learning with MATLAB®? Get started with a MATLAB machine learning example presented in an easy-to-follow tutorial format.

Learn more about machine learning with MATLAB:
Machine Learning Using Heart Sound Classification Example (22:03) - Video
Big Data with MATLAB - Overview
What Is Deep Learning? - Overview
Introducing Deep Learning with MATLAB - eBook
Parallel Computing on the Cloud with MATLAB - Overview
Predictive Analytics - Overview

Read more....

Introducing Machine Learning


https://youtu.be/0mK52UsOj-U

Google Open Online Education
This video is part of Google's Machine Learning Crash Course: https://g.co/machinelearningcrashcourse Machine Learning Crash Course is a fast-paced, practical introduction to machine learning. We recommend you view the video within the course to see the accompanying slides and documentation.

Conference in Machine Learning

March 10-14, 2019
Venue: Hemavans Högfjällshotell

Speakers:
Corinna Cortes, Head of Research, Google, USA
Edward Kennedy, Professor, Carnegie Mellon University, USA
Mattias Villani, Professor, Linköping University, Sweden

More information and registration: Winter Conference in Statistics 2019

måndag 12 november 2018

The promise and problems of including 'big data' in official government statistics

Official statistics help to shape a population’s 
sense of itself. Izumo Taisha/FlickrCC BY-SA
Qvintensen Webb
The Australian Bureau of Statistics (ABS) will soon announce the kinds of information it will collect in the next national census in 2021. If international trends are a guide, “big data” will comprise a growing part of ABS data collection and analysis.

Om helgens nyhet i SvD och deras undersökning om L sympatisörernas syn på regeringsbildningen

International Prize in Statistics Awarded to Stanford’s Bradley Efron

The International Prize in Statistics has been awarded to Bradley Efron, professor of statistics and biomedical data science at Stanford University, in recognition of the “bootstrap,” a method he developed in 1977 for assessing the uncertainty of scientific results that has had extraordinary impact across many scientific fields.

fredag 9 november 2018

New Wiley monograph on comparative survey methods

Pages are available here  online.