 Chapter six of our book is about sampling distributions and the idea behind this is You know everybody knows if you flip a coin ten times and you will usually get five heads But it could be higher. It could be lower if you flip it and get seven heads this time You don't necessarily expect to get seven heads the next time. There is inherent and inescapable Variability in this process. There's an element of randomness to it This is the central idea of sampling when you sample You're getting one possible outcome out of many possible random outcomes and the idea is to try to take those individual outcomes and Aggregate them into a sampling distribution and what's funny about that is you can make relatively Stable confident conclusions about an entire distribution, even if the individual elements have a large piece of randomness in them Now in terms of what we're going to talk about in this chapter We're going to talk about the sampling process how you actually do these repeated observations and build what's called a sampling Distribution we're going to talk about something called the central limit theorem Which describes the sampling distribution and its shape which approaches a normal bell curve It's mean which matches the original parameter that you're estimating and it's standard deviation Which in this context is called the standard error We'll also talk about z scores for sample means up to this point We've talked about z scores for one person at a time Now we're going to talk about it for a whole group of people and we'll look at how that can vary from one point To another this is our introduction to Hypothesis testing and this is how we can see the variability working in practice Now in terms of why we're going to talk about this first off, there's just this Inherent unavoidable drive to go beyond the data you have in front of you and to generalize to Another group of people or maybe to something in the near future Well, you can only do that if your data allow for generalization if you recognize the variability from one sample So one group of people to another sample, maybe a different group of people or the same people in the future It also serves that as sampling serves as the basis for every single chapter We're going to have from here on out. It's the basis for estimation. It's the basis for t-test analysis of variance for correlation and regression for The chi-square test it's there in all of them. It's also at the foundation of what makes psychology Really all of the behavioral sciences and social sciences Sciences as opposed to just you know random guesses or factoids about things that happened in the past It's this careful observation and an attempt to make valid inferences about the future that makes them sciences Now in terms of what you can do with this the what for of the chapter Well, the example of flipping coins isn't you know, it's a trivial one It's not something you're gonna do in the future, but in your real life Sampling variability and understanding how things vary from one situation to another and how even when Individual things vary you can still talk about the aggregate Well, let's say you're a therapist and you have one patient who's responding really well to treatment But another who's just struggling There may well be meaningful reasons for that difference But it also could be that the one person is just having a really good day or week and the other person is having a bunch of random hardships that that could explain it and that if you wait till the following week things could flip around you don't really know Even though you can talk about large groups of people if you're in the medical field You may have a lot of patients one day and very few the next day again There may be things in the community that explain that difference But it can also just be the random process like flipping coins and how many heads you get Or if you're looking at your retirement accounts, which may be invested in the stock market There may be a spike or a dip on one day where you get a lot of money or you lose a lot of money and That may or may not be a meaningful change. Usually it's not Chances are that the prices will return close to normal and hopefully resume the slow and steady upward trend that they tend to do but all of these are examples of how sampling and the Individual variability but the stability and predictability in large quantities can affect your life both in your regular work and in Psychological research and trying to better understand how people think feel and act