Comments by "Phil Davenport" (@phildavenport4150) on "Professor Dave Explains" channel.

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  541.  @renemunkthalund3581  If your "sample" is everyone, what you are doing is producing population parameters rather than statistics, which are based on samples derived from populations. The raw scores are irrelevant until standardized, at which time you calculate (arithmetic) mean and standard deviation. Given that test scores are normally distributed (i.e., the Gaussian distribution), you can show that any given raw score equates to a position on that scale, under the normal curve, and you can call the score "IQ" as it compares with others on the same scale. Normalized ability test raw scores, by definition, have an arithmetic mean of 100 and a standard deviation of (usually) 16, so a standardized score between 84 and 116 is considered to be "normal". Those scores falling at or below 84 are considered to be below normal, statistically, but the real meaning of this sort of thing has been the topic of discussion for a very long time. Psychs have been examining intellectual abilities in a much broader fashion for many years now, and the concept of IQ perhaps has rather less heuristic value than previously. Also, the concept of IQ as a simple linear scale has been considered not to be very helpful, especially when the complexity of intellectual tasks (e.g., the transition from arithmetic to abstract problem solving and conceptualization in math) becomes much greater, and requires different, rather than simply more of, the skills required to perform at lower levels. But I digress.
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