as we discussed earlier, we said that any type of calculations done has some level of uncertainty involved with it. This we termed experimental error. Now, here we're gonna talk about the two exact terms for the different types of errors that are commonly occurring, we're gonna say this first type of error is referred to as an indeterminant error. We're gonna say it occurs from uncontrollable variables In an experiment. It can occur at any time in a positive or negative magnitude, can never be corrected and is not reproducible. So for example, you take a weight, you know that it should wait 1010 g. But in some instances you get 9.8 g. Other instances you get 10.35 g, uh then you get 9.15 g. There is no consistency to the values here. They'll be too high by a certain value. Too low by certain value. So there is negative and positive magnitudes we call this random error. Now, the next type of error, which is also called determinant error Yeah, occurs from a problem with the machinery or a design flaw in the experiment. So occurs always in the same magnitude, can be corrected and is reproducible. So let's say you have a weight that's 10 g and you have a weight that's 12 g. You weigh the weight that's 10 g. And you get a reading of 10.5 g. You know that the standard weight is supposed to wait 10 g. But here it's giving us a magnitude that's 100.5 g too heavy. So if this is a systematic error, which is the type of error we're dealing with here, Then we should expect this 12 g weight to come out .05g too heavy. It's consistently giving us the same value, the same magnitude. It's always positive under certain certain certain circumstances or always negative and under other circumstances. So there's consistency with systematic error. The beauty of this type of error is that if you can find it you can correct it, thereby minimizing the type of error that will pop up when you do a calculation. So remember, all types of measurements have a level of uncertainty associated with them called experimental error. More specifically, we can talk about random error versus systematic error. Knowing this attempt to do the example question that's left here below. Don't worry. Just come back and see how I answer that same exact question. Okay.