Professor and class,

Collecting, analyzing, interpretating, and presenting data is statistics (Zach, 2022). Understanding your data is key to statistics, not over computing calculations (Holmes et al., 2017). Working on a medical/surgical unit, two different forms of data that I work with are daily blood pressure and temperature checks on my patients to assess their condition and overall health. Temperature checks can alert staff of an indication of infection, and or hypothermia. Blood pressure checks will provide knowledge of hypertension, hypotension, hypervolemia, hypovolemia, and sepsis. The average patient to nurse workload is eight to ten patients per shift. These are both classified as quantitative data related to numerical measurements and values. Blood pressure is usually classified as continuous due to having an infinite number of values within a range with a normal blood pressure of 120/80. Whereas temperatures are discrete due to being measured in finite increments such as tenths of a degree. Temperatures level of measurement is Interval due to being quantitative, can be ordered, meaningful differences between data can be collected and does not have an inherent zero, it is just a position on the scale. Blood pressure is measured on a ratio scale related to the numbers are equal in magnitude and rank on a numerical scale that has an absolute 0. The type of sampling used is cluster due to dividing the population into groups and selecting all the patients in one cluster but not the whole population.

Holmes, A., Illowsky, B., & Dean, S. (2017).

*Introductory Business Statistics*. Houston, TX: OpenStax CNX. Retrieved from https://openstax.org/details/books/introductory-business-statistics

Zach. (2022, August 29).

*The importance of statistics in Healthcare (with examples)*. Statology. https://www.statology.org/importance-of-statistics-in-healthcare/