The problem you're seeing is a fundamental issue with how computers typically do math. It is usually referred to as a floating-point error. Essentially, it comes down to the fact that it is very hard to represent .1 in binary (or .01, etc.), and you have to do some work to round the results a computer gives you to make it more accurate.
This recently came up on the team, and we have been discussing how to handle it. The Say bubbles do some rounding of numbers, but can lead to some inaccuracies. The think bubble gives slightly different results, and right now the team isn't in total agreement about which is preferred. You can try running your answers through the say bubble or the "round" blocks.
Here is some more information on floating point math: https://0.30000000000000004.com/.
And here's a video that gives a good explanation of the topic: https://www.youtube.com/watch?v=PZRI1IfStY0
Ar šis straipsnis buvo naudingas?
Tai puiku!
Dėkojame už jūsų atsiliepimą
Atsiprašome, kad negalėjome padėti
Dėkojame už jūsų atsiliepimą
Atsiliepimas išsiųstas
Dėkojame už jūsų komentarus ir pasistengsime pataisyti straipsnį