![]() Thus, when taking your average reaction time from 20 tries: The standard deviation for IQ in the general U.S. However scholar Arthur Jensen has shown that when you measure the mean reaction time repeatedly in college students (each one playing 20 times and taking the average simple reaction time for each student), most of the variability between individuals gets cancelled out and the standard deviation of the averaged out reaction times is only 29.23. Scholar Michael Woodley and his colleagues have argued that the population standard deviation for simple reaction time in Western countries is 160.4 ms, a truly colossal figure. The next thing we need to do is equate the standard deviation for simple reaction time with the standard deviation for IQ. In fact, this is a well known psychometric technique called equipercentile equating, and was used to norm the famous Mega test using SAT scores (see section 8.4.1 of the Prometheus MC Report for more details). Since this self-selection is g loaded, and since both reaction time and a 5 minute IQ test are probably both only moderately g loaded, it seems reasonable to equate them. But what they’re really self-selected for is intellectual interests and the internet access to pursue them. Some might argue that you can’t just equate the two figures because there’s no reason to assume chronometric players will be equally self-selected for reaction time as they are for IQ. Even though Thinkfast customers are not the same as visitors, it’s reasonable to assume that both populations have the same IQ, since they’re both self-selected internet users with an interest in reaction time. Well we can estimate the average IQ to be 117 because many years ago, a company called Braintainment sold a complex series of reaction time tests called “Thinkfast” and customers on their website had an average IQ of 117 based on a five-minute IQ test. In order to equate that to IQ, we need to know the average IQ of people who take that test. The average reaction time of those who take that test is 253 ms. PART 1: TECHNICAL DETAILS (SKIP TO THE PART 2) INTRODUCTION Automatic language identification, the problem of recognizing what language is being spoken, is a challenging research problem with important real-w.Eminent scientist and intelligence blogger Bruce Charlton once blogged about converting reaction times into IQ score equivalents, and now that blogger alcoholicwisdom has told this blog about a really user friendly reaction time test at, it’s time to explore this idea further. Statistical analyses of our results indicate that duration of the excerpt, familiarity with the language, and number of languages known are important factors affecting a subject's performance on the identification task. ![]() The subject population consisted of 10 native speakers of English and 2 speakers from each of the remaining 9 languages. In an effort to provide benchmarks for evaluating machine performance, we conducted perceptual experiments on 1-, 2-, 4- and 6-second excerpts of telephone speech excised from spontaneous speech utterances in this corpus. The advent of a public-domain ten-language corpus of telephone speech has made the evaluation of different approaches to automatic language identification feasible. ![]() There has been renewed interest in the field of automatic language identification over the past two years.
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