Type I error vs Type II error

Key Takeaways

in this lesson we will learn about the errors that can be made in hypothesis testing in general we can have two types of Errors type one error and type two error sounds a bit boring but this will be a fun lecture I promise first we will Define the problems and then we will see some interesting examples type one error is when you reject a true null hypothesis and is the more serious error it is also called a false positive the probability of making this error is Alpha the level of significance since you the researcher choose the alpha the responsibility for making this error lie solely on you type two error is when you accept a false null hypothesis the probability of making this error is denoted by Beta beta depends mainly on sample size and population variance so if your topic is difficult to test due to hard sampling or as high variability it is more likely to make this type of error as you can imagine if the data set is hard to test it is not your fault so type two error is considered a smaller problem we should also mention that the probability of rejecting a false null hypothesis is equal to 1 minus beta this is the researcher's goal to reject a false null hypothesis therefore 1 minus beta is called the power of the test generally researchers increase the power of a test by increasing the sample size this is a common table statisticians use to summarize the types of Errors now let's see an example that I heard from my professor back when I was studying statistics in University you are in love with this girl from the other class but are unsure if she likes you there are two errors you can make first if she likes you back and you don't invite her out you are making the type one error the no hypothesis in this situation is she likes you best back it turns out that she really did like you back unfortunately you did not invite her out because after testing the situation you wrongly thought the null hypothesis was false in other words you rejected a true null hypothesis and lost your chance it is a very serious problem because you could have been made for each other but you didn't even try now imagine another situation she doesn't like you back but you go and invite her out the null hypothesis is still she likes you back but this time it is false in reality she doesn't really like you back that is however after testing you accept the null hypothesis and wrongly go and invite her out she tells you that she has a boyfriend that is much older smarter and better at statistics than you and turns her back you made a type 2 error accepted a false null hypothesis however it is no big deal as you go back to your normal life without her and soon forget about this awkward situation hypothesis testing is usually like that you don't really want to make any of the two errors but it happens sometimes you should be aware that statistics is very useful but not perfect all right that's all from our love/ life/ statistics lesson thanks for watching for more videos like this one please subscribe