News:

In February, I am bringing my dataviz lecture to various cities: Atlanta (Feb 7), Austin (Feb 15), and Copenhagen (Feb 28). Click on the links for free registration.

I hope to meet some of you there.

***

On the sister blog about predictive models and Big Data, I have been discussing aspects of a dataset containing IMDB movie data. Here are previous posts (1, 2, 3).

The latest instalment contains the following chart:

Redo_scorebytitleyear_ans

The general idea is that the average rating of the average film on IMDB has declined from about 7.5 to 6.5... but this does not mean that IMDB users like oldies more than recent movies. The problem is a bias in the IMDB user base. Since IMDB's website launched only in 1990, users are much more likely to be reviewing movies released after 1990 than before. Further, if users are reviewing oldies, they are likely reviewing oldies that they like and go back to, rather than the horrible movie they watched 15 years ago.

Modelers should be exploring and investigating their datasets before building their models. Same thing for anyone doing data visualization! You need to understand the origin of the data, and its biases in order to tell the proper story.

Click here to read the full post.

 

 

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