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Showing posts with the label IQ

Code: Pinterest as a Publication Channel for Data Analytics

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More as an experiment, rather an attempt at sharing code and ideas, I created a Pinterest board devoted to my personal data analytics work, done with Python, R, or F#, as well as reviews of books, and was quite surprised with the result. The graphics could do with optimization, but otherwise...

Patents Per Capita and Hofstede's Cultural Dimensions

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Thinking about social dimensions and innovation, it occurred to me that there might be a relationship with masculinity, but then quickly dismissed it, considering it much more likely to be predicated on science/math education. Even then, other cultural elements might be more likely correlated. What follows is an exploration of various correlations with patents per capita. Although Hofstede's Cultural Dimensions did have a significant correlation with patents per capita, somewhat surprisingly, PISA scores by country, education, nor average IQ, had a strong relationship with patent production, although if Asia was included, statistically it would. Notes: I often exclude Asia from analyses, as the initial driver of this work was looking at cultures that are similar, to tease out social effects. That is also why I ignore looking at all countries, as some relationships across the entire world disappear when limited to just developed economies. As an example, the value of work and...

The IQ ~ Religion Matters Vector

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I was reminded this morning by an article, New Study: Religious People Are Less Smart but Atheists Are Psychopaths . but realized that there are many studies showing the religious to be less intelligent, but rarely is this ever published. It would 'bite' most of the population, liberal and conservative alike. Note : I plan on redoing this with more solid numbers, and possibly different measures of religiosity. Example Code # Correlations on ReligionMatters and Average IQ oecdData <- read.table("OECD - Quality of Life.csv", header = TRUE, sep = ",") iqVector <- oecdData$IQ religionMattersVector <- oecdData$ReligionMatters cor.test(iqVector, religionMattersVector) lm1 <- lm(iqVector ~ religionMattersVector) summary(lm1) # Plot the chart. plot(iqVector, religionMattersVector, col = "blue", main = "IQ ~ Religion Matters Vector" , abline(lm(religionMattersVector ~ iqVector),...