Analytical chemistry treats accuracy, how close a measurement actually is to the true value, and precision, how consistent repeated measurements are with each other, as genuinely separate properties rather than two words for the same idea. A measurement can be highly precise while being systematically wrong, an uncalibrated instrument giving tightly clustered but consistently offset readings, or accurate on average while being wildly inconsistent from one individual reading to the next, and telling those two failure modes apart matters because they need genuinely different fixes.
Systematic error and random error come from different sources and need different fixes
Systematic error, or bias, pushes measurements consistently in one direction, an uncalibrated balance that always reads slightly heavy is a systematic error, and repeating the same flawed measurement more times doesn't reveal or fix it, since every repeat is biased the exact same way. Random error instead scatters measurements unpredictably around the true value, caused by inherent noise in the measurement process itself, and averaging many repeated measurements genuinely does reduce random error's effect, since the scatter tends to cancel out over enough repetitions.
Statistical treatment turns repeated measurements into an honest estimate of uncertainty
Repeated measurements let a chemist calculate a result's standard deviation and a confidence interval around it, reporting a measurement together with its actual uncertainty rather than presenting a single number as if it were known exactly. Significant figures serve the same honesty function in a simpler form, communicating the real precision a measurement can actually support instead of implying false precision by writing down more digits than the measurement genuinely justifies.
What we're still unsure about
That accuracy and precision are genuinely separate properties, and that systematic and random error need different fixes, is well established, uncontroversial analytical chemistry. What's more genuinely difficult is that detecting and correcting systematic error in a specific measurement isn't simply a statistical calculation to run, since systematic error's whole defining feature is that repeating the same flawed measurement more times doesn't reveal it at all, genuinely catching it usually requires comparing results against a completely independent method or a certified reference standard, and chemists have occasionally discovered systematic errors that had gone undetected in a widely used method for years before someone happened to run that independent comparison.
This sits inside Error Analysis & Statistical Treatment of Data, one of seven topics in Analytical Chemistry, one of six domains in Chemistry, one of seventeen subjects the app can quiz you on.