Statistics Assignment: Analyzing Data Types and Sampling in Healthcare

This assignment provides an overview of basic statistical concepts, focusing on the application of these concepts within a healthcare context. The student analyzes two key variables: blood group, classified as qualitative or categorical data with a nominal level of measurement, and temperature, categorized as quantitative continuous data with an interval level of measurement. The assignment emphasizes the importance of understanding these data types for effective statistical analysis. Furthermore, it explores sampling techniques, advocating for stratified sampling as the preferred method for obtaining accurate and representative data in health facilities. Stratified sampling is chosen for its precision, accuracy, and ability to ensure representative samples, leading to cost savings. The assignment concludes by highlighting the benefits of stratified sampling over other methods such as convenience, cluster, systematic, and simple random sampling.

Running head: BASIC STATISTICS 1
Basic Statistics
Student Name
Professor’s Name
University Name
Date

BASIC STATISTICS 2
BASIC STATISTICS
Introduction
In statistics data refers to an actual value of a variable in the form of numbers and words. On the
other hand, variables refer to characteristics that can be determined from members of a
population. Different types of variables used in health facilities include temperature, age, height,
weight, ethnicity, blood group and respiration rate. The paper focuses on temperature and blood
group variables in a health facility and how they are statistically classified.
Classification of Two data types/Variables used in health facilities
Blood group
This is a variable that is used in a health facility to indicate the blood of patients. Blood group is
a qualitative or categorical data (Holmes, Illowsky, & Dean, 2019). This is because it
comprises of data that result from the categorizing or describing the blood group characteristics
or attributes of the members of a population in the health facility. The data from the variable
blood group are blood group AB+, O-, and B-. The level of measurement of this variable/data
type is nominal. This is because the data is used to label the variable but without a quantitative
value (Mishra, Pandey, Singh, & Gupta, 2018). Additionally, its nominal because the scale is
mutually exclusive; no overlaps are observed and there is no numerical significance in the data.
Example of the labels for the variable blood group are AB+, AB-, O- and B-.
Temperature
The variable temperature is applied in a health facility to determine the hotness or the coldness of
a patient’s body or body fluids. It is collected using a thermometer. Statistically, the variable
temperature is quantitative continuous (Holmes, Illowsky, & Dean, 2019). This is because it
comprises of data that result from measuring the temperature attributes of members of a

BASIC STATISTICS 3
population in the health facility. Besides, the variable has the capability of having fractions,
decimals, or irrational numbers. The level of measurement of the variable temperature is
interval. The variable has an interval level of measurement because it is a numeric scale where
the order and the exact difference between the data in the variable is known. For example, the
difference between 35 degree Celsius and 30 degree Celsius is known, and the latter is greater
than the former (Mishra, Pandey, Singh, & Gupta, 2018).
Preferred Method of sampling
Sampling is a technique applied in data collection that involve use of proportion rather than the
entire population. It is always aimed at reducing the cost. Samples are collected through random
sampling where every members of population have an equal chance of being selected. The best
method of sampling to get accurate data would be Stratified sampling.
In stratified sampling, the population is divided into groups called strata and a proportionate
number taken from each stratum (Holmes, Illowsky, & Dean, 2019). For example, a sample was
to be taken in a health facility for the temperature of patients with Hepatitis B, the patients would
have been divided into the strata’s, and a member from each stratum would be chosen as part of
the sample comprising of individuals from different stratum.
Compared to other methods of sampling such as convenience, cluster, systematic, and simple
random sampling which are either less accurate, time consuming, less representative of the
whole population or expensive, stratified sampling has a higher level of precision and accuracy,
hence can utilize a smaller sample size resulting to cost saving. Besides, stratified sampling
ensures that the data from the sample is representative of the whole population and also ensures
that sufficient sample points to support different analysis of subgroup is obtained.

BASIC STATISTICS 4
References
Holmes, A., Illowsky, B., & Dean, S. (2019). Introductory business statistics. OpenStax.
Mishra, P., Pandey, C., Singh, U., & Gupta, A. (2018). Scales of measurement and presentation
of statistical data. Annals of Cardiac Anesthesia, 21(4), 419. doi:
10.4103/aca.aca_131_18