• @owenfromcanada@lemmy.world
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    1455 months ago

    It depends on their window.

    If they include call volume data back to the Neolithic period in their calculations, then yes, call volumes are higher than average (the average being 0.001 calls per century, rounding up).

    Pretty sure that’s how they do the math.

    • @hemko@lemmy.dbzer0.com
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      235 months ago

      Or just let’s assume the phones are open 8 hours a day, 5 days a week. The average call volume would be drastically lower than during business hours

    • @Mirodir@discuss.tchncs.de
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      115 months ago

      It’s even simpler. A strictly increasing series will always have element n be higher than the average between any element<n and element n.

      Or in other words, if the number of calls is increasing every day, it will always be above average no matter the window used. If you use slightly larger windows you can even have some local decreases and have it still be true, as long as the overall trend is increasing (which you’ve demonstrated the extreme case of).

      • @dan@upvote.au
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        55 months ago

        It’s even simpler. They just lie about and always say it’s higher than average.

        • @Zink@programming.dev
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          25 months ago

          Yeah it’s fun seeing people figuring out which loophole companies use. Is it really anything other than they save a tiny bit of money by not giving a shit about your experience.

          • @Mirodir@discuss.tchncs.de
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            25 months ago

            Eh, nothing I did was “figuring out which loophole [they] use”. I’d think most people in this thread talking about the mathematics that could make it a true statement are fully aware that the companies are not using any loophole and just say “above average” to save face. It’s simply a nice brain teaser to some people (myself included) to figure out under which circumstances the statement could be always true.

            Also if you wanna be really pedantic, the math is not about the companies, but a debunking of the original Tweet which confidently yet incorrectly says that this statement couldn’t be always true.