class: middle background-image: url(data:image/png;base64,#LTU_logo.jpg) background-position: top left background-size: 30% # STM1001 [Topic 4B](https://bookdown.org/a_shaker/STM1001_Topic_4B_Sci/) Summary ## Designing a Study Part II ### La Trobe University This presentation complements the [Topic 4B readings](https://bookdown.org/a_shaker/STM1001_Topic_4B_Sci/) --- # Topic 4B: Designing a Study Part II ## In this week's readings: In this topic, we will discuss sampling considerations (external vailidity). Following an overview of sampling, we will consider various sampling methods, along with specific considerations for each type. --- # External validity (recap from last topic) .content-box-blue[ **Definition (External validity)** Externally validity refers to the ability to generalise the results to other groups in the population, apart from the sample studied.] -- **Example.** Suppose the population in a study is Queensland university students. The sample would be the students studied. The study is externally valid if the sample is a random sample from the population of students. The results will not necessarily apply to Queensland residents, but this has nothing to do with externally validity. External validity concerns how the sample represents the intended population in the RQ, which is Queensland university students. The study is not concerned with all Queensland residents. --- # The idea of sampling A RQ implies that every member of the population should be studied (the P in POCI stand for 'population'). However, being able to do so is very rare because of cost, time, ethics, logistics or practicality. Hence, a subset of the population (a sample) is almost always studied. -- .content-box-blue[ In research, the goal is to learn about the *population*, but only a *sample* can be studied. This subject is essentially about how to learn about a population based on an imperfect sample.] -- **Example** A study (based on Lipton et al. (1998)) of the effect of aspirin in treating headaches cannot possibly use every single human alive who might one day wish to take aspirin. -- Having seen that using a sample is necessary, other issues are raised: * *How* can we learn something useful about the *whole* population if only *some* of that population is studied? * *Which* individuals should be included in the sample? * *How many* individuals should be included in the sample be? --- <!-- # Precision and accuracy --> <!-- **Accuracy** refers to how close a *sample* estimate is to the *population* value (on average). **Accuracy** is related to the statistical concept of **bias**. **Precision** refers to how close all the possible sample estimates are likely to be (that is, how much variation is likely in the sample estimates). --> <!-- -- --> <!-- ```{r, echo = F, out.width="45%", out.height="35%", fig.align = "center"} --> <!-- if( knitr::is_html_output() ) { knitr::include_graphics("images/prec.jpg") --> <!-- } else { --> <!-- knitr::include_graphics("images/prec.pdf") --> <!-- } --> <!-- ``` --> <!-- --- --> # Random sampling methods .content-box-blue[ **Definition (Random)** In research and statistics, random means "determined completely by chance".] The results obtained from a random sample probably generalise to the population from which the sample is drawn; that is, *random samples* are likely to produce *externally valid* studies. See the [readings](https://bookdown.org/a_shaker/STM1001_Topic_4B_Sci/1.3-types-of-sampling.html) to learn more about the four types of random sampling: -- <img src="data:image/png;base64,#images/random.jpg" width="45%" height="35%" style="display: block; margin: auto;" /> --- # Non-random sampling methods A *non-random sample* requires some kind personal input. Examples of non-random samples include: * *Judgement sample*: Individuals are selected, based on the researchers' judgement, depending on whether the researcher thinks they are likely to be agreeable or helpful. For example, researchers may decided to survey people who are not in a hurry. * *Convenience sample*: Individuals are selected because they are convenient for the researcher. For example, researchers may gather data from their family and friends. * *Voluntary response* (self-selecting) sample: Individuals participate if they wish to. For example, a voluntary response survey, or a TV station call-in survey. -- .content-box-yellow[ Using a non-random sample means that the results may not generalise to the intended population: they probably do not produce externally valid studies.] --- name: menti class: middle background-image: url(data:image/png;base64,#menti.jpg) background-size: 115% # Have questions? ## Ask your computer lab demonstrator ## or discuss with your peers --- class: middle <font color = "grey"> These notes have been prepared by Illia Donhauzer. They are based on material written by Peter K. Dunn. Unless otherwise stated, material within this work is licensed under a Creative Commons Attribution-Non Commercial-Share Alike License <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA </a> </font>