Category: Data Science
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People Aren’t Getting Worse
Ever since I was in secondary school (high school in US terms) I have thought it is bizarre that people think that humans are getting worse. Adam Mastroianni and Dan Gilbert wrote a paper in Nature on this phenomenon which they call The Illusion of Moral Decline. In many ways, they have written the paper…
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Random Forests and Machine Learning
Scott Hartshorn has some useful accessible advice on all things analytics. Today I’ll look at his advice on random forests and machine learning. Machine Learning He starts by giving us a clear intuitive, rather than a formal, view of what machine learning (ML) is. He says that at their heart a lot of different ML…
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Explaining Clustering Simply Has Real Value
I was impressed by Annalyn Ng’s and Kenneth Soo’s short book Numsense. I have already discussed it in a prior post, see here. Today I will note how they discuss clustering. This is central to a lot of marketing analyses. Numsense Covers A Lot Of Basic Data Science The subtitle Data Science for the Layman…
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Comparing Text Classification Methods
Marketing research, especially academic research, now assesses a lot of unstructured text data. (Unstructured data is that which does not come in neat database/spreadsheet form of rows and columns). Classifying such text is a task that computers excel at. So, how do we go about comparing text classification methods to find which one best fits…
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A Framework For AI In Marketing
At the risk of stating the obvious artificial intelligence (AI) is a subject of great interest in marketing. Indeed, beyond marketing too at the moment. There is a lot of discussion of how companies can take advantage of the opportunities (and avoid the downsides). Raj Venkatesan and Jim Lecinski have a new book that sets…
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In Defense Of Robots And Their Judgments
A second post on the book, Noise, by Kahneman, Sibony, and Sunstein. For the first see here. The authors are experts in human judgment and they have a few useful comments in defense of robots and their judgments. Arguments Against, And For, Robots Noise is a book about the problems of variability in human judgment.…
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Understanding Data Analytics, And ‘Competitive Advantage’
Anil Maheshwari’s Data Analytics Made Accessible is a helpful book. Schools use it as a textbook and it has that feel. There is a lot of information there in a somewhat ‘just the facts’ sort of format. It should help with understanding data analytics. Useful Information To Aid In Understanding Data Analytics The book is…
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Costs Of Not Experimenting
Today I’ll look at the work of Uri Gneezy and John List. Specifically their book, The Why Axis. These are very well respected scholars and they are strong proponents of more real-world testing. Today I most want to highlight the idea that there are very sizable costs of not experimenting. Business Managers Under-Experiment The authors…
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Spoilers And Movie Box Office
What is the relationship between spoilers and movie box office? It is easy to tell a story that spoilers reduce anticipated enjoyment and so lower attendance at movie theaters. (I write during times of Covid so it is hard to imagine how anything reduces attendance further but you get the general idea). Is this the…
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Prejudice Against The Machine: Impact Of Chatbot Identity Disclosure
Whenever technology progresses a major question arises: What can technology do as well, or better, than humans? Since the luddites, and probably before, people reacted to technology with hostility. This raises the question whether machine learning algorithms can replicate (or outperform human behavior) but still be unpopular due to human reaction. A group of authors…
