Estimation deliberately trades exact accuracy for speed, and rounding is the specific technique for actually doing it, replacing a precise number with a simpler nearby one according to a fixed rule rather than carrying every exact digit through a calculation that doesn't actually need them. Knowing when an estimate is genuinely good enough for the job at hand, and when it genuinely isn't, matters considerably more in practice than simply being able to round a number correctly in the first place.
Rounding and estimation are tools for a fast, close-enough answer
Rounding follows a fixed, mechanical convention, typically rounding half up to the nearest value at whatever precision is actually needed, and estimation strategies built on top of it, front-end estimation, using compatible numbers that are easy to work with mentally, let you produce a quick, close approximation without carrying out the full, precise calculation. That's genuinely useful for a running total while shopping, or for a fast sanity check on whether a calculator's answer is roughly in the right range at all.
Whether estimation is safe to rely on depends entirely on the actual stakes
Estimation is fine, even genuinely useful, for a shopping-trip running total or a rough sanity check, situations where being slightly off costs nothing meaningful. It becomes genuinely risky when small rounding errors compound across many repeated calculations, or when an important decision hinges on a difference smaller than the rounding error itself, in both cases, an estimate that felt perfectly reasonable at each individual step can add up to a genuinely wrong final answer.
What we're still unsure about
That rounding follows a fixed convention and that estimation trades accuracy for speed is well established, uncontroversial arithmetic. What's genuinely a documented, real-world concern, not just a maths-class curiosity, is that individually tiny rounding errors can compound in a genuinely consequential way across a long chain of repeated calculations, a well documented issue in both engineering and financial computing, and there isn't one single universal rule for how much precision to actually carry through intermediate steps to avoid that, professional convention varies meaningfully by field, and the right amount of precision to keep is really a judgment call about how errors will specifically compound in that particular case, not a fixed formula.
This sits inside Estimation & Rounding, one of seven topics in Arithmetic, one of seven domains in Mathematics, one of seventeen subjects the app can quiz you on.