Application and interpretation of Public Health data-TOPIC 3 DQ 2
Topic 3: Introduction to Inferential Statistics and SPSS
QUESTION-TOPIC 3 DQ 2
Compare and contrast descriptive and inferential statistics. Discuss why both descriptive and inferential statistics are used in the analysis of public health data.
Descriptive and Inferential Statistics
Descriptive statistics help to summarize data by describing the connection between variables in a given sample (Kaur et al., 2018). Different types of descriptive statistics such as measures of central tendency, dispersion, frequency and position are used to summarize a multitude of sample data into a more specific way that is manageable. On the other hand, inferential statistics refer to the statistical methods used to conclude variables’ relations. Researchers observe sample data inferential and derive ideas based on the existing data (Haden, 2019).
Uses of Descriptive and Inferential Statistics
Descriptive statistics are an essential part of the original data analysis, thus providing a basis for evaluating variables with inferential statistics. Therefore, researchers must ensure good use of organized descriptive approaches to avoid misleading errors because statistical analysis results are vital in impacting public health. Proper use of descriptive statistics influences healthcare managers’ and providers’ effective implementation of health policies and programs (Kaur et al., 2018).
Inferential statistics categorically has an impact on the analysis of public health data. It helps investigators to conclude using a sample to a population of a study. In this case, inferential statistics is applicable in investigating differences among groups and the relationship among variables of a sample (Guetterman, 2019). The final results are vital in making appropriate decisions suitable for improving public health.
Public health data will always rely on descriptive and inferential statistics to stabilize its essence on population health. The statistical techniques help develop the methodologies, approaches, and theoretical framework used in public health data analysis. Thus, it is essential for all those involved in research work to ensure good use of both statistics in their study. Besides the chronological approaches, both statistics make public health data simpler and manageable through their breakdown of information.
Guetterman, T. C. (2019). Basics of statistics for primary care research. Family medicine and community health, 7(2). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6583801/
Haden, P. (2019). Inferential statistics. The Cambridge Handbook of Computing Education Research, 133-172. https://faculty.cs.nku.edu/~waldenj/classes/2019/spring/csc640/lectures/inferential-statistics.pdf
Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60. https://www.ijam-web.org/article.asp?issn=2455-5568;year=2018;volume=4;issue=1;spage=60;epage=63;aulast=Kaur&__cf_chl_managed_tk__=pmd_Z274Zup8WD7Bf8OQt3A78jgZdbFvum9689bn.p9eHvE-1632151157-0-gqNtZGzNAyWjcnBszQp9