In the previous presentation we reviewed different types of quantitative research samples in research, sampling in research design. Now we need to collect data to feed the quantitative research samples in research, sampling in research design that we selected in this presentation. I will cover the first step of data collection which is simply so. Why do we need sampling in an ideal world. We will collect information samples in research, sampling in research from all people that we are interested in for example if we want to understand. ASU students the population of our study will be all the ESU students or if you want to know undergraduate students in the United States your population will be all undergraduate students in the country. Would it be possible to collect information samples in research, sampling in research on all of them. How much time and resources would we need to do. So for those reasons. We will use samples in research, sampling in researchwhich is subset of your population and subject in your study. The samples in research, sampling in researchwill be the people who are in your study who you collect information samples in research, sampling in research from what you eventually want to understand and make conclusions about is population. You observe things from your sample. Then generalize your findings from the samples in research, sampling in researchto your population. This is what. I meant when I said our goal of quantitative research samples in research, sampling in research is to channelize the findings therefore how you select your samples in research, sampling in researchwhich is sampling is really important and the sampling framework. You choose will be based on how you can access to. Your potential simple sampling framework can be mainly two types first is random sampling and then the other is non-random or non probability simply random sampling as the term speaks is randomly choosing your samples in research, sampling in researchfrom your population. The first is simple random sampling. Let’s say you put everyone’s name tag in a box and take out one tag at a time until you reach to your designed samples in research, sampling in researchsize. Of course this process nowadays is done with computer. The second type of random sampling is a systematic sampling. You first list the people in your population and choose every caithe individual like this picture you can select second person first from the beginning of the number then after that select every third person from the previous number on the other hand strata sampling allows you to recognize different characteristics of people in your sample.
First you separate the population into non-overlapping groups called strata such as male and female shown in this example and then obtain a simple random samples in research, sampling in researchfrom each group in some cases. Your population might consist of several groups. These subgroups are called. Cluster and each cluster represents the population therefore cluster sampling. Makes you first randomly choose the groups or clusters for example academic programs that consist of a university then select individuals from each strata. So the four sampling frameworks. We just reviewed randomly select sample. That means each individual in your population has the same probability to be chosen although random sampling is ideal because if people are chosen randomly with equal chances of being in samples in research, sampling in researchthen your samples in research, sampling in researchwill be most similar to the nature of your population. However this is not always a handy option and a lot of times people use non-random where nonprobability sampling. This means that in your sampling says not everyone has same probability to be selected. First type is convenience sampling just as the name self explains you draw your samples in research, sampling in researchfrom part of the population that is close to your reach for example. Let’s say you wanted to know how strongly Americans would support free tuition so our population is all Americans and drawing a random samples in research, sampling in researchmight be a very difficult task in that case. You can draw your samples in research, sampling in researchfrom people around you your friends colleagues from your work your professor and etc. Then what do you think about using this approach in terms of generalizing the results well as you see. The samples in research, sampling in researchselected is really representative. And you have to acknowledge this when you use convenient samples in research, sampling in researchsecond is snowball sampling. Basically you use word of mouth you find the initial subjects and ask them to identify another potential subject who also meets the criteria of the research samples in research, sampling in research for example.
You wanted to understand work experience of female faculty on campus. You can contact five female professors across the campus and ask them to recommend their peers who are also female faculty on campus again. This frame might also suffer. In terms of the representativeness of the population. Third type of non random sampling is purposive. Simply when you have particular characteristics or dimensions of people that you believe as a good fit for the research samples in research, sampling in research compared to other individuals you can purposely select people who qualify for that criterion. An example can be when a research samples in research, sampling in researcher wants to learn about first-generation college student in this case rather than randomly selecting samples in research, sampling in researchfrom like any college students. The research samples in research, sampling in researcher purposefully would choose only first-generation students. Finally your population might be consists of people with different traits. If you want to have your samples in research, sampling in researchto reflect the composition of population given those traits. You can assemble your samples in research, sampling in researchto have the same proportions of individuals as the entire population with respect to known characteristics. Let’s say you want to understand students diversity experience on a su campus. You will want to make your samples in research, sampling in researchto reflect the ratio at the next composition of a ESU students. For example if about 50 percent of the students are white followed by 18.5 of Hispanic and 6.8 percent of Asian and 4% of african-american. You will want to make your samples in research, sampling in researchcomposition similar to these numbers so you will need to consider who your population is and how you will select your samples in research, sampling in researchwhen you consider sampling. You will need to consider why particular random or non-random methods. We reviewed is better than other options again. Random sampling might be beneficial for improving representativeness of the samples in research, sampling in researchand generalizability of the findings to your population.
But it involves a lot of time and costs sometimes to better reflect your population. You may need to purposefully choose non-random sampling methods so the key takeaway is to choose our sampling frame. The best serves your research samples in research, sampling in research purpose. Were trying to reduce potential bias and error due to the nature of your sample. Another important dimension for sampling is samples in research, sampling in researchsize. The samples in research, sampling in researchsize determines how generalizable the findings from the samples in research, sampling in researchis. You can refer to samples in research, sampling in researchsize calculator. That is available already or look at other studies to judge if you have enough samples in research, sampling in researchsize for a given population you may want to go for a larger samples in research, sampling in researchif your population different in many dimensions and want to break down data into more categories and if you concern about a low response rate now you have basic concepts that are related to sampling during our face-to-face meeting. We will discuss the choice of research samples in research, sampling in research design that fits to your research samples in research, sampling in research questions and workshop your sampling strategies. The following two videos will discuss how you can collect data from your samples in research, sampling in researchalso. I recover how to frame your questions. If you want to conduct a survey study these activities will be also covered in the class. So watch those videos before you come to the class.
Where to find great research papers?
Various great research journals such as Global Research Letters are a great option and way to help you look up impactful research papers with a great format. Here, you will find a number of various research papers that are provided and made available to you in the journal, which will help you write your own paper.
You can very easily find papers on a variety of topics at Global Research Letters, which will help you with your own research work and understanding of writing and publishing research papers properly. With access to so many amazing research papers, you can practice and learn the process of writing research papers and their importance.