would say that in an introductory course at this level that we briefly look at 6 methods of data collection and that among researchers and scholars 5 of them are considered to be sampling techniques but I think it is appropriate to mention the 6th method of data collection in this same breath anyway.
In our online text book on pages 16-17 the authors discuss simple random sampling, stratified sampling, cluster sampling, systematic sampling, and convenience sampling.
Convenience sampling is bar far the weakest of all these methods and leads to the greatest potential and opportunities for various forms of statistical bias in the resulting sample. So in real life practice, convenience sampling should be avoided at all costs, and simple random sampling is often thought of as a bit of a “gold standard” in statistics and quantitative research. But I can see or visualize in real life practice why once in a while that stratified sampling might be a pretty good idea and approach, so to speak, for example.
The 6th form of data collection that I want to mention here is a census. The reason that a census is different from the 5 types of sampling mentioned above is that a census literally is “everyone” while the other 5 forms of data collection above definitely involve “less than everyone.”
Please see the following slides to see some pictures of some of these sampling techniques.
Please feel free to look around in the online text book and on the internet at large to see info about what a census is and to Post about it in one of your Week One Posts.
Sometimes when Folks talk about “research methods” part of what they are talking about is “the organization of the study.” But there is much more to it than that and the “organization of the study” “issue” is not addressed much in the slides that follow here but it is addressed a little bit. As you go on to take additional and more advanced and more detailed courses in quantitative research and data analysis and statistics and probability, knowing and understanding “the organization of the study” will become more and more important to you being able to understand and follow the types of things that you will be studying and learning about in those future courses.
So in this course you are not held very accountable for what is on many of the slides that follow here, but on the other hand understanding some of what is on the slides that follow here will help your overall understanding and comfort and confidence during this course here.
For example in this course here, it is very important to understand the difference between a sample and a population. It is also very important to understand the difference between a statistic and a parameter.
Thanks Friends and the slides that follow here should give you a reasonable basis and foundation for approaching the upcoming Weeks 2-8 of the course.
Thanks and Best Wishes Friends !!
n the Mental Health and addiction field data that we measure are reports of anxiety. As a variable, anxiety is a qualitative measure as it can only be reported as a subjective experience. We use quantitative data to support reports of anxiety such as measuring a blood pressure and respirations per minute. After reading about the measurement of variables, I believe that an anxiety rating would be Ordinal as it is ranked on a scale of 1 to 10 however it has no mathematical application. (week 1 Lesson: Introduction to Statistics: Data Collection and Data Concepts).
If I needed to gather data on how different medications best treat the symptom of anxiety, I would use Stratified sampling as studying people who take a specific medication for anxiety would mean I would have to locate and study a portion of a population (people who have anxiety vs those who seek medical treatment to manage anxiety).
reference
week 1 Lesson: Introduction to Statistics: Data Collection and Data Concepts
