 So let's dive into the language of statistics. What comes to mind when the typical human thinks of the word population? Lots of people. And does it have to be people? Things, viruses, computers, hard disks, what have you? So a definition like all the things. Yes, that's what's coming to mind. Something like that, the collection of all the items that we're interested in. We've got this emphasis in the same place where you wanted to put it. All the things. Let's shift the emphasis to where it ought to be. Here, the population is what we are interested in for the purpose of making our current decision. In fact, this is going to be a legal contract in statistics. In that sense of the truth, the whole truth and nothing but the truth, the population, the whole population, nothing but the population is what is interesting for your decision. Only the entire population is interesting to you. Anything else but the entire population is by legal contract boring. So please make sure that all your definitions reflect this and that you have carefully and properly specified what is actually interesting to you. So please make sure that you've defined your population to be that thing that is interesting for your decision. Let's make it visual. I love unrealistic examples. All my examples are unrealistic. Here, we have some forest floating on some plains in space. Cool. These trees are our whole population. So we are getting desperately excited about these trees. Any tree that you don't see pictured here, dead to you. This tree right here, boring. It is not your whole population. Only all of them together are interesting to you. What is a sample? A sample is any subset, any sub-collection from our population, like those trees labeled orange or those. Either is a sample. One might be a better sample than the other or both samples. An observation is one single measurement in the sample like this blue one over here.