“When the time value is small, the error is also small. But the problem with a percentage error is that, as the value gets bigger, the error grows with it.”
[Humble PI: A Comedy of Maths Errors, Matt Parker]
Rounding a number is a quite simple method to approximate some complicated numbers, leading to easy calculation and good memory. However, such approximation makes a percentage error which makes a big problem when the value is big. Moreover, error grows bigger when multiplying this approximated number many times. To reduce a percentage error for mass production, in the late 20th century, many companies have focused on quality management such as Six Sigma. Specifically, companies have made continuous efforts to reduce a (percentage) error, leading to successful and predictable process results. In data science, to obtain high-fidelity prediction with big numbers, they have kept a significant digit as many as they can.
What about individuals? we often think that we made a 100% effort for my task but we actually made a 95% effort and rounded off. This approximation will make a problem in the future. What? you can say that the 95% effort is high enough to say 100%. Is it true? Let’s take an example, you usually complete a task with a 95% effort (here, say, a success rate) and you have 20 tasks now. Then, the probability that you complete all 20 tasks successfully is 35.8%. However, if you make a 99% effort for each task, then the probability will be 81.8% (and 98% with a 99.9% effort). This example shows that a small different percentage makes a big difference, and we agree that we should complete more than 20 tasks to achieve success in your life. That’s why we should do our best (close to a 100% effort) every time to reach your goal in life.
Everybody makes DATA 