Simply Statistics – StatsBlogs

The data deluge means no reasonable expectation of privacy – now what?

Simply Statistics — Tue, 23 Jul 2019 00:00:00 +0000

Today a couple of different things reminded me about something that I suppose many people are talking about but has been on my mind as well.

The idea is that many of our societies social norms are based on the reasonable expectation of privacy. But th...

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More datasets for teaching data science: The expanded dslabs package

Simply Statistics — Fri, 19 Jul 2019 00:00:00 +0000

Introduction
We have expanded the dslabs package, which we previously introduced as a package containing realistic, interesting and approachable datasets that can be used in introductory data science courses.
This release adds 7 new datasets on climat...

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Research quality data and research quality databases

Simply Statistics — Wed, 29 May 2019 00:00:00 +0000

When you are doing data science, you are doing research. You want to use data to answer a question, identify a new pattern, improve a current product, or come up with a new product. The common factor underlying each of these tasks is that you want to u...

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I co-founded a company! Meet Problem Forward Data Science

Simply Statistics — Mon, 20 May 2019 00:00:00 +0000

I have some exciting news about something I’ve been working on for the last year or so. I started a company! It’s called Problem Forward data science. I’m pumped about this new startup for a lot of reasons.

My co-founder is one of ...

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Generative and Analytical Models for Data Analysis

Simply Statistics — Mon, 29 Apr 2019 00:00:00 +0000

Describing how a data analysis is created is a topic of keen interest to me and there are a few different ways to think about it. Two different ways of thinking about data analysis are what I call the “generative” approach and the “analytical” approa...

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Tukey, Design Thinking, and Better Questions

Simply Statistics — Wed, 17 Apr 2019 00:00:00 +0000

Roughly once a year, I read John Tukey’s paper “The Future of Data Analysis”, originally published in 1962 in the Annals of Mathematical Statistics. I’ve been doing this for the past 17 years, each time hoping to really understand what it was he was ta...

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Interview with Abhi Datta

Simply Statistics — Mon, 01 Apr 2019 00:00:00 +0000

Editor’s note: This is the next in our series of interviews with early career statisticians and data scientists. Today we are talking to Abhi Datta about his work in large scale spatial analysis and his interest in soccer! Follow him on Twitter at @dat...

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10 things R can do that might surprise you

Simply Statistics — Wed, 13 Mar 2019 00:00:00 +0000

Over the last few weeks I’ve had a couple of interactions with folks from the computer science world who were pretty disparaging of the R programming language. A lot of the critism focused on perceived limitations of R to statistical analysis.
...

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Open letter to journal editors: dynamite plots must die

Simply Statistics — Thu, 21 Feb 2019 00:00:00 +0000

Statisticians have been pointing out the problem with dynamite plots, also known as bar and line graphs, for years. Karl Broman lists them as one of the top ten worst graphs. The problem has even been documneted in the peer reviewed literature. For exa...

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Interview with Stephanie Hicks

Simply Statistics — Mon, 18 Feb 2019 00:00:00 +0000

Editor’s note: For a while we ran an interview series for statisticians and data scientists, but things have gotten a little hectic around here so we’ve dropped the ball! But we are re-introducing the series, starting with Stephanie Hicks. ...

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The Tentpoles of Data Science

Simply Statistics — Fri, 18 Jan 2019 00:00:00 +0000

What makes for a good data scientist? This is a question I asked a long time ago and am still trying to figure out the answer. Seven years ago, I wrote:

I was thinking about the people who I think are really good at data analysis and it occurred to...

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How Data Scientists Think – A Mini Case Study

Simply Statistics — Wed, 09 Jan 2019 00:00:00 +0000

In episode 71 of Not So Standard Deviations, Hilary Parker and I inaugurated our first “Data Science Design Challenge” segment where we discussed how we would solve a given problem using data science. The idea with calling it a “design challenge” was...

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The Netflix Data War

Simply Statistics — Wed, 19 Dec 2018 00:00:00 +0000

A recent article in the Wall Street Journal, “At Netflix, Who Wins When It’s Hollywood vs. the Algorithm?” by Shalini Ramachandran and Joe Flint details some of the internal debates within Netflix between the Los Angeles-based content tea...

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The Role of Theory in Data Analysis

Simply Statistics — Tue, 11 Dec 2018 00:00:00 +0000

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 head...

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The role of academia in data science education

Simply Statistics — Thu, 01 Nov 2018 00:00:00 +0000

I was recently asked to moderate an academic panel on the role of universities in training the data science workforce. I preceded each question with opinionated introductions which I have fused into this blog post. These are weakly held opinions so p...

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Guest Post: Galin Jones on criteria for promotion and tenture in (bio)statistics departments

Simply Statistics — Thu, 11 Oct 2018 00:00:00 +0000

Editor’s Note: I attended an ASA Chair’s meeting and spoke about ways we could support junior faculty in data science. After giving my talk Galin Jones, Professor and Director of Statistics at University of Minnesota, and I had an interesti...

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The economic consequences of MOOCs

Simply Statistics — Mon, 08 Oct 2018 00:00:00 +0000

tl;dr check out our new paper on the relationship between MOOC completion and economic outcomes!

Last Monday we launched our Chromebook Data Science Program so that anyone with an internet connection, a web browser, and the ability to read and follow ...

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Chromebook Data Science – a free online data science program for anyone with a web browser.

Simply Statistics — Mon, 01 Oct 2018 00:00:00 +0000

The Johns Hopkins Data Science Lab has been teaching massive online open courses for more than 5 years now. During that time we’ve reached more than 5 million learners who want to break into the number one rated job in America.

While we have bee...

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The complex process of obtaining Puerto Rico mortality data: a timeline

Simply Statistics — Fri, 28 Sep 2018 00:00:00 +0000

Rolando Acosta and I recently posted a manuscript on bioRxiv describing the effects of Hurricane María, based on an analysis of mortality data provided by the Demographic Registry. I was also an author on a paper published in May based on a survey of 3...

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Divergent and Convergent Phases of Data Analysis

Simply Statistics — Fri, 14 Sep 2018 00:00:00 +0000

There are often discussions within the data science community about which tools are best for doing data science. The most recent iteration of this discussion is the so-called “First Notebook War”, which is well-summarized by Yihui Xie in his blog pos...

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