Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

October 27, 2013

Lectures on scientific computing with Python

Filed under: Python,Skepticism — Patrick Durusau @ 5:35 pm

Lectures on scientific computing with Python by J.R. Johansson.

From the webpage:

A set of lectures on scientific computing with Python, using IPython notebooks.

Read only versions of the lectures:

To debunk pitches, proposals, articles, demos, etc., you will need to know, among other things, how scientific computing should be done.

Scientific computing is a very large field so take this as a starting point, not a destination.

Trouble at the lab [Data Skepticism]

Filed under: Data,Data Quality,Skepticism — Patrick Durusau @ 4:39 pm

Trouble at the lab, Oct. 19, 2013, The Economist.

From the web page:

“I SEE a train wreck looming,” warned Daniel Kahneman, an eminent psychologist, in an open letter last year. The premonition concerned research on a phenomenon known as “priming”. Priming studies suggest that decisions can be influenced by apparently irrelevant actions or events that took place just before the cusp of choice. They have been a boom area in psychology over the past decade, and some of their insights have already made it out of the lab and into the toolkits of policy wonks keen on “nudging” the populace.

Dr Kahneman and a growing number of his colleagues fear that a lot of this priming research is poorly founded. Over the past few years various researchers have made systematic attempts to replicate some of the more widely cited priming experiments. Many of these replications have failed. In April, for instance, a paper in PLoS ONE, a journal, reported that nine separate experiments had not managed to reproduce the results of a famous study from 1998 purporting to show that thinking about a professor before taking an intelligence test leads to a higher score than imagining a football hooligan.

The idea that the same experiments always get the same results, no matter who performs them, is one of the cornerstones of science’s claim to objective truth. If a systematic campaign of replication does not lead to the same results, then either the original research is flawed (as the replicators claim) or the replications are (as many of the original researchers on priming contend). Either way, something is awry.

The numbers will make you a militant data skeptic:

  • Original results could be duplicated for only 6 out of 53 landmark studies of cancer.
  • Drug company could reproduce only 1/4 of 67 “seminal studies.”
  • NIH official estimates at least three-quarters of publishing biomedical finding would be hard to reproduce.
  • Three-quarter of published paper in machine learning are bunk due to overfitting.

Those and more examples await you in this article from The Economist.

As the sub-heading for the article reads:

Scientists like to think of science as self-correcting. To an alarming degree, it is not

You may not mind misrepresenting facts to others, but do you want other people misrepresenting facts to you?

Do you have a professional data critic/skeptic on call?

October 24, 2013

Introductory Econometrics using Quandl and R

Filed under: R,Skepticism — Patrick Durusau @ 6:41 pm

Introductory Econometrics using Quandl and R

From the webpage:

Econometrics applies mathematical and statistical tools to reveal measurable relationships in real world data. Though the ability to find relationships in quantitative data is useful in many professions and academic disciplines, knowledge and experience with econometric processes is limited to those with a college or university background in the subject. However, this does not need to be the case. Modern statistical software has become more powerful, but also much easier to use. In this tutorial, we introduce one of the most useful econometric tools: linear regression. Using detailed examples and clear explanations, we will begin our tutorial with the basic concepts of regression analysis and end with the more complex multiple regression model.

Regression and multiple regression models are used in many domains. Picking up the technique and its terminology will help you recognize poor or deceitful use of it.

Data skepticism is a useful skill whether you are developing topic maps or not.

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