Posts Tagged ‘ science ’

Reading Everything is Obvious by Duncan Watts

February 15, 2017
By
Reading Everything is Obvious by Duncan Watts

In his book, Everything is Obvious (Once You Know the Answer): Why Common Sense Fails, Duncan Watts, a professor of sociology at Columbia, imparts urgent lessons that are as relevant to his students as to self-proclaimed data scientists. It takes only nominal effort to generate narrative structures that retrace the past, Watts contends, but developing lasting theory that produces valid predictions requires much more effort than common sense. Watts’s is…

Read more »

Pre-processing data is not just about correcting errors

January 30, 2017
By
Pre-processing data is not just about correcting errors

Exploration of IMDB rating data, by Kaiser Fung, founder of Principal Analytics Prep

Read more »

Apparently Hollywood does not recycle action-movie plots. The data said so, so it must be right

January 25, 2017
By
Apparently Hollywood does not recycle action-movie plots. The data said so, so it must be right

Today I continue to explore the movie dataset, found on Kaggle. To catch up with previous work, see the blog posts 1 and 2. One of the students came up with an interesting problem. Among the genre of action movies, are there particular plot elements that are correlated with box office? This problem is solvable because the dataset contains a variable called "plot keywords" lifted from IMDB. Plot keywords are…

Read more »

Good models + Bad data = Bad analysis

January 18, 2017
By
Good models + Bad data = Bad analysis

Example showing how to diagnose bad data in data science models

Read more »

Chopped legs, and abridged analyses

December 27, 2016
By
Chopped legs, and abridged analyses

Reader Glenn T. was not impressed by the graphical talent on display in the following column chart (and others) in a Monkey Cage post in the Washington Post: Not starting column charts at zero is like having one's legs chopped...

Read more »

Books on Scala for statistical computing and data science

December 22, 2016
By
Books on Scala for statistical computing and data science

Introduction People regularly ask me about books and other resources for getting started with Scala for statistical computing and data science. This post will focus on books, but it’s worth briefly noting that there are a number of other resources available, on-line and otherwise, that are also worth considering. I particularly like the Coursera course … Continue reading Books on Scala for statistical computing and data science

Read more »

Scala for Data Science [book review]

December 22, 2016
By
Scala for Data Science [book review]

This post will review the book: Scala for Data Science, Bugnion, Packt, 2016. Disclaimer: This book review has not been solicited by the publisher (or anyone else) in any way. I purchased the review copy of this book myself. I have not received any benefit from the writing of this review. Introduction On this blog … Continue reading Scala for Data Science [book review]

Read more »

Inspired by water leaks

December 19, 2016
By
Inspired by water leaks

For me, 2016 is a year of water leaks. I was forced to move apartments during the summer. (Blame my old landlord for the lower frequency of posts this year!) That old apartment was overrun by water issues. In the past four years, there were two big leaks in addition to annual visible "seepage" in the ceiling. The first big leak ruined my first night back from Hurricane Sandy-induced evacuation.…

Read more »

This election forecasting business

November 15, 2016
By
This election forecasting business

If you live in the States, and particularly a blue state, in the last year or two, it has been drilled into your head that Hillary Clinton was the overwhelming favorite to win the Presidential election. On the day before the election, when all the major media outlets finalized their "election forecasting models," they unanimously pronounced Clinton the clear winner, with a probability of winning of 70% to 99%. One…

Read more »

Reader’s Guide to the Power Pose Controversy 3

November 2, 2016
By

This is the third and final post about the controversy over statistical analysis used in peer-reviewed published scholarly research. Most of the new stuff are covered in post #2 (link). Today's post covers statistical issues related to sample size, which is nothing new, but it was mentioned in Amy Cuddy's response to her critics and thus I also discuss it here. In post #2 (link), I offer the following mental…

Read more »


Subscribe

Email:

  Subscribe