Feb 23, 2024 Week 1 Discussion: Basic Statistics Data Used in Everyday Life
I 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.
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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
Hi Class and Professor Smith,
Statistics is a powerful tool that can be used to analyze and predict behaviors of several systems, from weather forecasts to stock market analysis. Obviously, health sciences are not excluded from the application of statistics, for every medical advancement there is a statistical study supporting and validating the idea.
Recently, due to the COVID pandemic there have been hundreds of new studies trying to understand the viral pathogenesis, symptomatology, or analyze the patients’ response to different treatments (among other things).
In the study “Novel Use of Home Pulse Oximetry Monitoring in COVID‐19 Patients Discharged From the Emergency Department Identifies Need for Hospitalization”, pulse oximetry is used to predict the risk of intensive care.
Pulse oximetry is, by its numerical nature, quantitative data. It can be further classified as continuous. One can argue that because the vast majority of pulse oximeters have a precision on the integer level (no decimals) the data can be classified as discrete. Nevertheless, with a precise enough instrument, measurements within a decimal interval can be made. Additionally, for the level of measurement, pulse oximetry falls under the Ratio category due to the fact that the zero value means a complete absence of oxygenation.
It is important to notice that the sampling technique is not necessarily dependent on the chosen variable; the study objective is the defining factor. For this research, the authors reported a convenience sampling as they considered only suspected cases of COVID, and keep only the data of those who tested positive for COVID-19.
Another example of a variable used in the medical field is race, as shown in the paper “Racial Bias in Pulse Oximetry Measurement”. In this study, the relation of pulse and arterial oximetry measurements is correlated to race (Black or white only). It was found that “black patients have three times the frequency of occult hypoxemia that was not detected by pulse oximetry” (Sjoding 2020)
In this scenario race is a qualitative type of data as no numerical value is associated to race. As for the level of measurement, race belongs to the nominal scale as it cannot be ordered in a meaningful way.
Similar to the former study, the sampling method used was based on convenience. The study involved patients who were receiving supplemental oxygen at the University of Michigan Hospital (from January through July 2020) and patients in intensive care units at 178 hospitals (from 2014 through 2015).
Holmes, A. B., Illowsky, B., Dean, S. L., OpenStax College,, & OpenStax (Nonprofit organization),. (2017). Introductory business statistics.
Shah, S., Majmudar, et al. (2020). Novel Use of Home Pulse Oximetry Monitoring in COVID‐19 Patients Discharged From the Emergency Department Identifies Need for Hospitalization. Academic Emergency Medicine, 27(8), 681–692. https://doi.org/10.1111/acem.14053Links to an external site.
Sjoding, M. W., Dickson, R. P., Iwashyna, T. J., Gay, S. E., & Valley, T. S. (2020). Racial Bias in Pulse Oximetry Measurement. New England Journal of Medicine, 383(25), 2477–2478. https://doi.org/10.1056/NEJMc2029240
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