Blog Archives

Data as an antidote to aggressive overconfidence

January 21, 2015
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A recent NY Times op-ed reminded us of the many biases faced by women at work. A followup op-ed  gave specific recommendations for how to conduct ourselves in meetings. In general, I found these very insightful, but don't necessarily agree with the recommendations that women should "Practice Assertive Body Language".  Instead, we should make an effort to judge

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Gorging ourselves on "free" health care: Harvard’s dilemma

January 20, 2015
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Gorging ourselves on "free" health care: Harvard’s dilemma

Editor's note: This is a guest post by Laura Hatfield. Laura is an Assistant Professor of Health Care Policy at Harvard Medical School, with a specialty in Biostatistics. Her work focuses on understanding trade-offs and relationships among health outcomes. Dr. Hatfield received her BS in genetics from Iowa State University and her PhD in biostatistics from the University

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Statistics and R for the Life Sciences: New HarvardX course starts January 19

January 12, 2015
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Statistics and R for the Life Sciences: New HarvardX course starts January 19

The first course of our Biomedical Data Science online curriculum starts next week. You can sign up here. Instead of relying on mathematical formulas to teach statistical concepts, students can program along as we show computer code for simulations that illustrate the main ideas of exploratory data analysis and statistical inference (p-values, confidence intervals and

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On how meetings and conference calls are disruptive to a data scientist

December 22, 2014
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Editor's note: The week of Xmas eve is usually my most productive of the year. This is because there is reduced emails and 0 meetings (I do take a break, but after this great week for work). Here is a repost of one of our first entries explaining how meetings and conference calls are particularly disruptive in

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Kobe, data says stop blaming your teammates

December 12, 2014
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Kobe, data says stop blaming your teammates

This year, Kobe leads the league in missed shots (by a lot), has an abysmal FG% of 39 and his team plays better when he is on the bench. Yet he blames his teammates for the Lakers' 6-16 record. Below is a plot showing that 2014 is not the first time the Lakers are mediocre during Kobe's

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Genéticamente, no hay tal cosa como la raza puertorriqueña

December 8, 2014
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Genéticamente, no hay tal cosa como la raza puertorriqueña

Editor's note: Last week the Latin American media picked up a blog post with the eye-catching title "The perfect human is Puerto Rican". More attention appears to have been given to the title than the post itself. The coverage and comments on social media have demonstrated the need for scientific education on the topic of

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Thinking Like a Statistician: Social Media and the ‘Spiral of Silence’

December 2, 2014
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Thinking Like a Statistician: Social Media and the ‘Spiral of Silence’

A few months ago the Pew Research Internet Project published a paper on social media and the ‘spiral of silence’. Their main finding is that people are less likely to discuss a controversial topic on social media than in person. Unlike others, I  did not find this result surprising, perhaps because I think like a statistician.

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HarvardX Biomedical Data Science Open Online Training Curriculum launches on January 19

November 25, 2014
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We recently received funding from the NIH BD2K initiative to develop MOOCs for biomedical data science. Our first offering will be version 2 of my Data Analysis for Genomics course which will launch on January 19. In this version, the course will be turned into an 8 course series and you can get a certificate in each one

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Data Science Students Predict the Midterm Election Results

November 12, 2014
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Data Science Students Predict the Midterm Election Results

As explained in an earlier post, one of the homework assignments of my CS109 class was to predict the results of the midterm election. We created a competition in which 49 students entered. The most interesting challenge was to provide intervals for the republican - democrat difference in each of the 35 senate races. Anybody

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538 election forecasts made simple

November 4, 2014
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Nate Silver does a great job of explaining his forecast model to laypeople. However, as a statistician I've always wanted to know more details. After preparing a "predict the midterm elections" homework for my data science class I have a better idea of what is going on. Here is my best attempt at explaining the ideas of

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