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  2. Answering TikTok: What does a '30% chance of rain ... - AOL

    www.aol.com/weather/answering-tiktok-does-30...

    Cornish said the concept is plain and simple: "It is the probability that at least 0.01 of an inch of precipitation will fall on your rooftop if you live in the forecast area. That's about enough ...

  3. Ten-code - Wikipedia

    en.wikipedia.org/wiki/Ten-code

    California Penal Code sections were in use by the Los Angeles Police Department as early as the 1940s, and these Hundred Code numbers are still used today instead of the corresponding ten-code. Generally these are given as two sets of numbers [ citation needed ] —"One Eighty-Seven" or "Fifty-One Fifty"—with a few exceptions such as "459 ...

  4. EU’s unwinnable price war with Chinese EVs summed up ... - AOL

    www.aol.com/finance/eu-unwinnable-price-war...

    Rhodium expects the EU to implement a 15-30% tariff on Chinese EVs following its probe. But even at the higher range, the group says, this isn’t likely to deter automakers from shipping to the ...

  5. Radar beacon - Wikipedia

    en.wikipedia.org/wiki/Radar_beacon

    Radar beacon. Racon signal as seen on a radar screen. This beacon receives using sidelobe suppression and transmits the letter "Q" in Morse code near Boston Harbor (Nahant) 17 January 1985. Radar beacon (short: racon) is – according to article 1.103 of the International Telecommunication Union's (ITU) ITU Radio Regulations (RR) [1 ...

  6. Coupon collector's problem - Wikipedia

    en.wikipedia.org/wiki/Coupon_collector's_problem

    In probability theory, the coupon collector's problem refers to mathematical analysis of "collect all coupons and win" contests. It asks the following question: if each box of a given product (e.g., breakfast cereals) contains a coupon, and there are n different types of coupons, what is the probability that more than t boxes need to be bought ...

  7. Bayes' theorem - Wikipedia

    en.wikipedia.org/wiki/Bayes'_theorem

    A factory produces items using three machines—A, B, and C—which account for 20%, 30%, and 50% of its output respectively. Of the items produced by machine A, 5% are defective; similarly, 3% of machine B's items and 1% of machine C's are defective. If a randomly selected item is defective, what is the probability it was produced by machine C?