Peer 1

Basic Statistics Data Used in Everyday Life

In healthcare research and practice, data collection involves both qualitative and quantitative variables. Two examples are pain rating scores and ethnicity.

Pain Rating Scores Pain is often measured using a numeric rating scale (0–10) (Nugent et al., 2021). This is a quantitative variable because it expresses pain intensity numerically and allows for mathematical operations, such as calculating mean pain levels across a population. The level of measurement is ordinal, since the numbers reflect order (for example, 8 indicates more pain than 5), but the intervals between scores are not guaranteed to represent equal differences in perceived pain. For example, the difference between a pain score of 2 and 4 may not equal the difference between 6 and 8.

Ethnicity Ethnicity refers to categories based on cultural, linguistic, or ancestral backgrounds. This is a qualitative variable because it classifies individuals into groups rather than expressing numerical values. Its level of measurement is nominal, since categories such as Hispanic, African American, or Asian represent distinct groups without inherent order. Unlike ordinal or interval data, nominal categories cannot be ranked or mathematically manipulated.

Sampling Approach When gathering data on these variables, researchers can use different sampling techniques. For pain rating scores, systematic sampling can be effective, where every nth patient in a clinic is selected to provide data, ensuring coverage across time and patient flow. For ethnicity, stratified sampling is appropriate, where the population is divided into strata (for example, ethnic groups), and participants are proportionally sampled from each stratum. This ensures representation of diverse groups and prevents bias toward majority populations (LoBiondo-Wood & Haber, 2022).

Overall, recognizing the type and level of measurement for variables ensures appropriate statistical analysis and accurate interpretation in health research.

References

Nugent, S. M., Lovejoy, T. I., Shull, S., Dobscha, S. K., & Morasco, B. J. (2021). Associations of pain numeric rating scale scores collected during usual care with research administered patient reported pain outcomes. Pain Medicine (Malden, Mass.), 22(10), 2235–2241. https://doi.org/10.1093/pm/pnab110Links to an external site. LoBiondo-Wood, G., & Haber, J. (2022). Nursing research: Methods and critical appraisal for evidence-based practice (10th ed.). Elsevier. 

Peer 2

In healthcare, two important things we always check are blood pressure and pain scores. Blood pressure is a number measured in mmHg so it’s quantitative. It’s considered ratio data because there’s a true zero and we can say one number is truly double another like 120 is twice 60. Pain scores are also numbers but they are more about ranking. A pain score of 8 means worst than 4 but the distance between those numbers isn’t the same for everyone. This makes them ordinal data. If I were collecting this data for a project, I could use systematic sampling, like asking every 5th patient admitted to the unit. I like that this connects to nursing.    

Reference  

Illowsky, B., & Dean, S. (2023, December 13). Ch. 1 Introduction – Introductory Statistics 2E | OpenStax. https://openstax.org/books/introductory-statistics-2e/pages/1-introduction [9/6, 18:43] jaimie meadoh NPH Aug 25: Follow-up Post Instructions Respond to at least one peer. Further the dialogue by providing more information and clarification.

Your responses to other students can explain additional analyses that could be done with the variables they selected. Consider confounding variables, discrete or continuous data, the effects of outliers, etc.

Writing Requirements Minimum of 2 posts (1 initial & 1 follow-up) APA format for in-text citations and list of references

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