Stumbled Upon
 List of Countries by Average Wage
Here's something fun from CNN: a global wage calculator [l]. Compare your salary income with the average salary income in your country and abroad. CNN didn't make up the wage data: they took the average wage statistics from the International Labor Organization [l] which itself obtained the wages from data given by the companies to the governments. Wage or salary income only includes regular payments given to employees by their companies and does not include investment income, stocks income, property income, etc. In the major economies, the average annual gross (before tax) salary income was as follows in 2014:
 Country Average Gross Annual Wage in 2013 PPP$USA 42,972 South Korea 40,791 Germany 38,910 Australia 38,464 France 37,307 Canada 36,434 Japan 34,621 UK 32,640 Italy 32,625 South Africa 31,702 Russia 19,646 Saudi Arabia 15,420 Turkey 13,957 China (public sector) 13,547 Brazil 12,560 Mexico 8,159 India 7,057 Indonesia 5,226  03.11.15  Myers-Briggs Personality Types According to the Myers-Briggs theory, everyone can be categorized as being one of 16 possible personality types. Take the test on 16personalities.com [l] and see what type you belong to. I'm an INTJ [l]. I was surprised at how accurate this turned out to be considering the seemingly simple questionnaire.. Here is a list of the different Myers-Briggs types [l] and their corresponding Keirsey types [l] along with their corresponding roles and temperaments:  Myers-Briggs Keirsey Role Temperament % ESTJ [l] Supervisor [l] Administrator Guardian 8-12 ISTJ [l] Inspector [l] Administrator Guardian 10-14 ESFJ [l] Provider [l] Conservator Guardian 9-13 ISFJ [l] Protector [l] Conservator Guardian 9-14 ESTP [l] Promoter [l] Operator Artisan 4-10 ISTP [l] Crafter [l] Operator Artisan 4-6 ESFP [l] Performer [l] Entertainer Artisan 4-10 ISFP [l] Composer [l] Entertainer Artisan 5-10 ENFP [l] Champion [l] Advocate Idealist 7 INFP [l] Healer [l] Advocate Idealist 4 ENFJ [l] Teacher [l] Mentor Idealist 2-5 INFJ [l] Counselor [l] Mentor Idealist 1-2 ENTJ [l] Fieldmarshal [l] Coordinator Rational 2-4 INTJ [l] Mastermind [l] Coordinator Rational 1-2 INTP [l] Architect [l] Engineer Rational 1-5 ENTP [l] Inventor [l] Engineer Rational 2-5  Comparative Price Levels The OECD compiles every month a comparison of the price levels between countries [l]. The data is obtained by dividing the PPP exchange rate (for actual private consumption) [l] by the nominal exchange rate. This can give a good idea of the cost of living in other OECD countries at the present time.  List of Countries by Publications and Citations Scimago offers a comparison between countries on the basis of the number of scientific papers published [l]. The publications are limited to those appearing in SCOPUS [l] ranked journals (journals of reasonable quality). Here is a list of selected countries on the basis of number of citations between 2012 and 2014 for the papers published in 2012:  Country Citations Citations per capita Australia 396,312 0.0157 UK 966,659 0.0151 Canada 527,481 0.0151 Germany 873,264 0.0109 USA 1,742,766 0.0107 France 580,535 0.0088 Italy 479,404 0.0080 Korea 273,592 0.0055 Japan 511,289 0.0040 China 1,046,924 0.0008 Russia 94,744 0.0007 India 259,891 0.0002  03.12.15  Highly Cited Researchers Thomson-Reuters publishes every year a list of the 3000 or so most highly cited researchers in the world [l]. The number of highly-cited researchers per country in 2014 was as follows:  Region Highly-Cited Researchers USA 1667 EU15 974 China (excl. HK) 135 Japan 102 Canada 89 Korea 24 Hong Kong 22 Singapore 18 India 12 Taiwan 11 Russia 7  List of Languages by Speech Information Rate Different languages have different spoken information rates not only due to how fast they are spoken but also due to their different grammar and different concentration of homonyms. In Table 1 in Ref. [1] and in Figure 1 in Ref. [2], different languages such as French, Mandarin, English, Korean, etc are compared on the basis of information density (information per syllable), syllable rate (syllables per second) and information rate (information per second):  Language Information Density Syllable Rate Information Rate English 0.91 (± 0.04) 6.19 (± 0.16) 1.08 (± 0.08) French 0.74 (± 0.04) 7.18 (± 0.12) 0.99 (± 0.09) Spanish 0.63 (± 0.02) 7.82 (± 0.16) 0.98 (± 0.07) Italian 0.72 (± 0.04) 6.99 (± 0.23) 0.96 (± 0.10) Mandarin 0.94 (± 0.04) 5.18 (± 0.15) 0.94 (± 0.08) German 0.79 (± 0.03) 5.97 (± 0.19) 0.90 (± 0.07) Korean 0.62 (± 0.02) 6.95 0.83 Japanese 0.49 (± 0.02) 7.84 (± 0.09) 0.74 (± 0.06)  [1] F Pellegrino, C Coupé, and E Marsico. “A cross-language perspective on speech information rate”, Language, Volume 87, Number 3, September 2011 [l]. [2] Yoon-Mi Oh, F Pellegrino, E Marsico, and C Coupé. “A Quantitative and Typological Approach to Correlating Linguistic Complexity”, Proceedings of the 5th Conference on Quantitative Investigations in Theoretical Linguistics, University of Leuven, 12-14 September 2013 [l].  03.16.15  Calculating Probabilities — Hypergeometric Function Calculating odds and probabilities is not always trivial. Take the new PNU presidential election process for instance. Starting from this year, there is a new “indirect” election system imposed by the Ministry of Education and in which the 1000 or so PNU faculties are represented by 33 voting professors. Such 33 voting professors are chosen randomly among the 1000 faculties. Knowing that there are only 12 foreign faculty members, what are the odds that there will be at least 1 foreign professor among the 33 voting professors? To find the probabilities for such a problem, use the hypergeometric function [l] with the following input:  Field Value Population size 1000 Number of successes in population 12 Sample size 33 Number of successes in sample$(x)$1 This would yield a probability$P(x = 1)$of 27.6% that exactly one foreign prof is a voting member, and a probability$P(x \ge 1)$of 33.3% that one or more voting members are foreign.  06.04.15  Grid Convergence Index (GCI) The Grid Convergence Index (GCI) gives the grid-induced error associated with numerical results obtained on a certain grid [l]. The GCI needs to be used with some care thus as it often leads to a rosy prediction of the grid-induced error because it is based on Richardson extrapolation which may not be valid for flows with discontinuities (such as shockwaves or contact discontinuities). One thing to verify when using the GCI is that the solution obtained is within the asymptotic range of convergence. This can be done by checking if the constant$C$$$C=\frac{\cal E}{\Delta x^p}$$ as well as the order of accuracy$p$remain the same as the grid is refined (with$\cal E$being the error and$\Delta x$the mesh spacing on a given grid). If the so-obtained$p$s and$C$s differ from each other substantially, it's necessary to further refine the grid until the solution falls within the asymptotic range of convergence. Only then can the GCI be used to estimate the grid-induced error.  07.12.15  Handbook of Academic Titles Michael I. Shamos, a Professor in the School of Computer Science at Carnegie Mellon University compiled a very handy list of the various titles given to professors and researchers working in universities. For instance, what is the difference between a “research professor” and an “associate professor”? Do these titles confer tenure? Explanations to the various academic titles are given on the Carnegie Melon website [l].  07.27.15  Minimum Wage in OECD Countries as of 2013 Here's a Bloomberg chart giving the net minimum wage in international dollars (PPP) amongst the OECD countries as of 2013 (after all compulsory deductions such as social security payments, medicare, pension plan, etc): Read more about it on Bloomberg [l], or see the raw data for gross minimum wage for all countries on wikipedia [l].  07.30.15  Average Salaries in the Chaebols Here is a chart from the Korea Herald showing the average salary of the workers in the chaebols [l] in millions of won per year: Note: 1 million won is about 850\$US or 1100\$CAD.  09.08.15  Mapping Tree Density at a Global Scale An article entitled “Mapping Tree Density at a Global Scale” appeared in the journal “Nature” this month discussing the tree density worldwide [l]. One figure showing tree density is striking: In the latter, the white dots represent areas with year-round ice cover, the brown dots represent areas with no trees, while the dark green dots represent areas with the highest tree concentration. The land proportion composed of areas with little or no trees is alarmingly large — about half of the world's forests have been destroyed or irremediably damaged since the advent of agriculture 10000 years ago. But what is more worrisome is that half of this destruction took place in the last 50 years.. Still today, it seems we haven't learned our lesson: we continue to cut down more trees than we plant as we have been doing for generations. If we do not change our living habits soon and start caring for our environment, the entire planet will be treeless within a couple of centuries.  1, 2 , 3 Next • PDF 1✕1 2✕1 2✕2 $\pi\$