Machine Learning

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Say that we are studying the correlation between voltage and a light bulb's brightness. Amazingly, we always know exactly what voltage we are using, but we haven’t been so lucky when measuring bulb brightness. Here are our options: A perfectly accurate sensor taped to another light bulb, twice as bright as the one we’re measuring. We can’t get rid of the second light bulb; we don’t know why but the sensor won’t work without it. A primitive but effective device from the 1840’s, rather like a thermometer. It works, but a human must estimate its readings. A completely broken machine. It always just reads zero. Actual state-of-the-art technology, no quirks attached. If we always run the light bulb with the same voltage and measure the brightness ten times, which of these devices will collect data with the highest standard deviation, all else being equal?

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