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I want to do a quick video on something that you're likely to see in a statistics class and that's the notion of a type 1 error type type 1 type 1 error and all this error means is that you've rejected this is the error of rejecting let me just in a different color rejecting rejecting the null hypothesis even though it is true even though it is true so for example and a lot of the and actually all of the hypothesis testing examples we've seen we start assuming that the null hypothesis is true we assume we always assume that the null hypothesis is true and given that the null hypothesis is true we say ok if the null hypothesis is true then the mean is usually going to be equal to some value so we create some distribution assuming that the null hypothesis is true it normally has some mean value right over there and then we have some sent we have some statistic we have some statistic and we are seeing if the null hypothesis is true what is the probability of getting that statistic or getting a result that extreme or more extreme then that's that statistic so let's say that the statistic gives us some value over here and we say gee you know what there's only it there's only I don't know there might be a 1% chance there's only a 1% probability there's only a 1% probability of getting a result that that extreme or greater and then with if that's I guess low enough of a threshold force we will reject we will reject the null hypothesis so in this case in this case we will so let's say let's say that actually let's think of it this way let's say that 1% is our threshold we say look we're going to assume that the null hypothesis is true there's some threshold that if we get and if we get a value any more extreme than that value there's less than a 1% chance of that happening so let's say we're looking at sample means and we get a sample mean that is way out here we say well there's less than a 1 cent chance of that happening given that the given that the null hypothesis is true so we are going to reject the null hypothesis so we will reject the null hypothesis now what does that mean though let's say that this area the probability of getting a result like that or that or that much more extreme is just this area right here so that's let's say that's half a percent or maybe I can write it this way let's say it's half a percent and because it's so unlikely to get a statistic like that given assuming that the null hypothesis is true we decide to reject the null hypothesis or another way to view it is there's a point five percent chance that we have made a type 1 error in rejecting the null hypothesis because if the null hypothesis is true there's a point five percent chance that this is that that this could still happen so in rejecting it we would make mistake there's a point five percent chance we've made a type 1 error I just want to clear that up hopefully they clarified it for you it's sometimes a little bit confusing but we're going to use what we learn in this video and the previous video to now tackle an actual example