Read through the most famous quotes by topic #statistic
J. E. Littlewood, a mathematician at Cambridge University, wrote about the law of truly large numbers in his 1986 book, "Littlewood's Miscellany." He said the average person is alert for about eight hours every day, and something happens to the average person about once a second. At this rate, you will experience 1 million events every thirty-five days. This means when you say the chances of something happening are one in a million, it also means about once a month. The monthly miracle is called Littlewood's Law. ↗
The value for which P=0.05, or 1 in 20, is 1.96 or nearly 2; it is convenient to take this point as a limit in judging whether a deviation ought to be considered significant or not. Deviations exceeding twice the standard deviation are thus formally regarded as significant. Using this criterion we should be led to follow up a false indication only once in 22 trials, even if the statistics were the only guide available. Small effects will still escape notice if the data are insufficiently numerous to bring them out, but no lowering of the standard of significance would meet this difficulty. ↗
Out of a hundred people: Those who always know better- 52 Doubting every step- all the rest Glad to lend a hand if it doesn’t take too long- as high as 49 Always good, because they can’t be otherwise- 4 maybe 5 Able to admire without envy- 18 Living in constant fear of something or someone- 77 Capable of happiness- 20 something tops Harmless singly, savage in crowds- half at least Wise after the fact- just a couple more than wise before it Taking only things from life- 30 (I wish I were wrong) Righteous- 35, which is a lot Righteous and understanding- 3 Worthy of compassion- 99 Mortal- 100 out of 100 (Thus far this figure still remains unchanged.) ↗
#statistics #wisdom #life
Another mistaken notion connected with the law of large numbers is the idea that an event is more or less likely to occur because it has or has not happened recently. The idea that the odds of an event with a fixed probability increase or decrease depending on recent occurrences of the event is called the gambler's fallacy. For example, if Kerrich landed, say, 44 heads in the first 100 tosses, the coin would not develop a bias towards the tails in order to catch up! That's what is at the root of such ideas as "her luck has run out" and "He is due." That does not happen. For what it's worth, a good streak doesn't jinx you, and a bad one, unfortunately , does not mean better luck is in store. ↗
#luck #math #probability #statistics #math