Chapters 11 and 12 (and 13 if there is time)

1. A Harkening to Earlier Days, Complete With Homework Assignment, Quiz Bulletpoints, and More Than 20 Slides Chapters 11 and 12(and 13 if there is time)

2. Random does not mean “unexpected”. Humans are not random. Like, ever. Randomness refers to there being a collection of known possible outcomes, but which cannot be determined ahead of time. The best way to randomly select something is to write down the options you have on separate pieces of paper, put them in a hat, shake the hat up, and select however many you need without looking. Chapter 11

3. A study creates a few groups: A population – This is the entire group of people you will be drawing conclusions about, including both those you are testing and those you are not. A sample – Unless you are conducting a census, this will be different than your population. Chapter 12 – Anatomy of a Sample

4. The sampling frame – This is the collection of all people within the population who could be part of the sample. In a perfect study, the sampling frame would be the population, but in practice, it tends to narrow the population down a bit. For example, if the study is done through a website survey, the sampling frame becomes the people in the population with internet access. Chapter 12 – Anatomy of a Sample

5. Any groups in the population which are not a part of the sampling frame form the undercoverage bias, which we will get back to later in the slideshow. In the real world, most of the time, the sampling frame will be smaller than the population, and the sample itself will only be a part of the sampling frame. Chapter 12 – Anatomy of a Sample

6. When we have a pile of data, we can summarize it with various values. • We tend to focus on measures of center and spread, such as mean, median, standard deviation, and IQR. • Both the population and the sample have these values. • Unless we are doing a census, the sample and the population will have different values, but they should be close to each other. Chapter 12 – The Next Distinction

7. For a sample we call these summarizing numbers statistics. For a population we call these summarizing numbers parameters. In practice, we do not know parameters and so we have to use the statistics we get from the sample to make inferences about the parameters. Chapter 12 – The Next Distinction

8. Parameters will generally focus on the mean of some population value or else the percent of the population that is a certain way. In order to distinguish this from the sample value, we will usually use the word “true” in front of the mean or the percent. For example, if we were studying the heights of American males, the parameter would be described as “the true mean height of American males”. Chapter 12 – The Next Distinction

9. The most ideal method of sampling is called a simple random sample. • You take everyone in the population and randomly select however many you need. • The downside of this method is that you need a full roster of the population, which is often difficult to get or maybe even impossible. • This usually only happens in textbooks. Chapter 12 – Sampling Methods

10. The two next most common sampling methods are cluster sampling and stratified sampling. These methods involve splitting the sample into groups, which is actually often convenient as data frequently already comes in groups. For example, schools can be broken down by homeroom, people in the U.S. can be broken down by state, city, county, or zip code…and so on. Chapter 12 – Sampling Methods

11. In stratified sampling, you pull a few people out of each group. • These groups, by the way, are called strata. • Stratum is the singular term. • In cluster sampling, you select a few groups and sample each person in those strata. • Sometimes these can be merged into a combination of the two, which is called multistage sampling. Chapter 12 – Sampling Methods

12. There is also systematic sampling, which involves taking a list and selecting every n-th person. This is only a valid method if you have a list in a randomized order, but since most lists are in alphabetical order, this tends to be an inferior method. Chapter 12 – Sampling Methods

13. Finally, there is convenience sampling, which is sampling based on whoever or whatever was convenient to study. Don’t do it! Portal to HELL!!! Metaphorically, that is. Still, though, it is gateway to potentially unmitigated badness. Chapter 12 – Sampling Methods

14. There are three types of bias we talk about in this course. The first one is undercoverage, which is where an entire subpopulation is not getting fairly represented. This generally happens when the sampling frame excludes part of the population. Sometimes it cannot really be helped, so in practice the goal is to minimize the amount of avoidable undercoverage bias. Chapter 12 – Bias

15. Next is nonresponse bias, which is a bias caused by people not responding. More specifically, it means people who you intended to be a part of the sample not responding (as opposed to people being part of an undercovered group). Sometimes it is by choice and we call it voluntary response bias, and other times it was not a matter of choice, in which case it is still nonresponse bias, but it does not have a secondary label. Chapter 12 – Bias

16. Finally there is response bias. This is when the study is done by someone, with certain wording, in a particular situation, or something else is going on which influences they way people respond. Chapter 12 – Bias

17. Studies have two different timeframes, two different types, and two different methods of measurement. The two timeframes are prospective and retrospective. Retrospective studies are done after the fact by reviewing historical data or by measuring things that have already been affected by whatever the study is focused on. Chapter 13 – Some Key Pairs

18. Prospective studies identify subjects ahead of time and measure the data as it occurs. When people talk about a long term study, it is generally prospective. Prospective studies are generally preferable, since the data is more likely to be accurate if you measure it as it occurs. Chapter 13 – Some Key Pairs

19. The first type of study is an observational study. Not to put too fine a point on it, but this is a study where you are simply observing what happened or is happening. Observational studies can be either prospective or retrospective. Chapter 13 – Some Key Pairs

20. The other type of study is an experiment. In an experiment, effort is made to control as much of the situation as possible while imposing various conditions to see how they affect the outcome. Experiments are always prospective. Experiments are necessary to establish cause and effect. We will talk about experiments much more in chapter 13. Chapter 13 – Some Key Pairs

21. The first data collection method is survey. There are lots of flaws with this but it still sees a lot of use because the other method, though more reliable, is often impractical. The other method is direct measurement. Consider favorite color…I could do direct measurement by showing people colors while they are in an MRI machine to determine which one is their favorite. Chapter 13 – Some Key Pairs

22. Ch 12: 2 problems from 1 to 10 and also problems 11 and 12. Due Friday Read Chapter 13 through the top of 298. As a heads up, I will be assigning the rest of chapter 13 as reading for Thursday, so now would be an excellent time to get behind, if that was your goal. Quiz Friday over chapters 11, 12, and parts of 13. Assignments

23. Know how to randomize. Know the different types of bias. Know the difference between controlled variables and blocking variables and be able to suggest some of each in a given scenario. Know the difference between statistical significance and practical significance. Know the difference between factors, levels, and treatments. Quiz Bulletpoints