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Summary And Descriptive Statistics Discussion

Summary And Descriptive Statistics Discussion

Table showing statistics from the National Cancer Institute on lung and bronchus cancer cases across ethnicities.

The table above outlines the number of lung and bronchus cancer cases across various ethnicities per 100,000 people.  Analyzing the data using measures of central tendency, the group with the highest average cases is the Blacks with 70.06875, followed by whites with 62.75 cases, American Indians follow with 43.28, the Asian Pacific Islanders are next with 38. 51 cases and the group with the least cases is the Hispanic group with 31.49 (Yadav, Singh & Gupta, 2019; NCI,2018). The median also projects a similar trend with the Blacks leading and the Hispanics coming last. In terms of occurrence of a similar number of cases across the years, it’s only Pacific Islanders, Hispanics and Whites who have more than one similar number of cases. The Pacific Islanders have 36.6 cases in 2011 and 2013, Hispanics had 34.1 cases in 2001 and 2002 while  Whites had 65.8 cases in 2004 and 2006.

Analysis of the data using measures of variation offers deeper insights (Deshpande, S., Gogtay, & Thatte, 2016). For instance, the number of lung and bronchus cancer cases among Pacific Islanders and Hispanics has not fluctuated much but rather seems to occur within a close range across years because their Variance is 5.68 and 8.40 respectively. However, the number of cases among Blacks indicates a downward trend with cases reducing from 77.8 in 2000 to 57.4 in 2015. The Blacks, therefore, have a high variance score which is 45.42.  The number of cases among American Natives has also reduced since their variance score is equally high at 27.72, followed by Whites whose variance is 26.162. The trend is also similar looking at the standard deviation since a figure close to zero indicates low dispersion from the mean, while a higher number indicates highly variables data. the standard deviation is higher among blacks at 6.74, followed by American Natives at 5.26, whites at 5.11, Hispanics at 2.90 and lastly Pacific Islanders at 2.38.


Deshpande, S., Gogtay, N. J., & Thatte, U. M. (2016). Measures of central tendency and dispersion. Journal of the Association of Physicians of India, 64, 64-66.

National Cancer Institute (2018) Lung and bronchus cancer. Retrieved from January 8, 2019, from https://seer.cancer.gov/explorer/application.php?site=47&data_type=1&graph_type=2&compareBy=race&chk_sex_1=1&chk_race_5=5&chk_race_4=4&chk_race_3=3&chk_race_6=6&chk_race_2=2&chk_age_range_1=1&chk_data_type_1=1&advopt_precision=1&advopt_display=1&showDataFor=sex_1_and_age_range_1_and_data_type_1

Yadav, S. K., Singh, S., & Gupta, R. (2019). Measures of Central Tendency. In Biomedical Statistics (pp. 41-52). Springer, Singapore.


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Topic 1 DQ 1

Aug 15-17, 2022

Discuss the historical application of statistics in the field of health care. Describe an example, other than Florence Nightingale’s contributions, where statistical application has greatly influenced or changed health care operations or practice.



Health Statistics provide information for understanding, monitoring, improving, and planning the use of resources to improve people’s lives, provide services and promote their well-being. Statistics are used in healthcare for research, quality improvement, inequalities in healthcare, risk analysis, inventory management and cost, resource utilization, patient length of stay, patient satisfaction, clinical trials, morbidity and mortality, effects of new treatments, measuring change, laboratory analysis, education, and much more.

Statistics have been utilized in healthcare since at least the 19th century. Florence Nightingale used a statistical approach to decrease the mortality rate of British troops in Crimea. Her meticulous records were a key to present-day statistical quality measurement, and she was an innovator in the collection, tabulation, interpretation, and graphical display of descriptive statistics. She named her visual data display a “Coxcomb,” known today as a pie- chart (Sheingold & Hahn, 2014). Clara Barton applied the same analysis in the United States during the Civil War.

Louis Pasteur applied statistics in his research of microbes and the “germ theory” to create penicillin. This evidence led to the wide-scale adoption of antiseptic practices by physicians and hospitals throughout Europe and eventually in the U.S. Pasteur’s research also led to the development of “pasteurization,” which utilizes heat to destroy harmful microbes in perishable food while leaving the food undamaged (Sheingold & Hahn, 2014).

Dr. Rupert Blue was responsible for providing leadership in America during the worst disease outbreak in U.S. history. The Influenza Pandemic of 1918 killed fifty (50) million or 1/5 of the world’s population, representing more people than died during World War I. During the Influenza Pandemic, Dr. Blue’s quality tools were quarantine, mandatory medical exams for all immigrants entering the country, communication in the form of weekly newsletters that contained information about the latest outbreaks, and the results of influenza research conducted at the Hygienic Laboratory which continues to exist today (Sheingold & Hahn, 2014).

The medical records during the 1918 influenza pandemic inform how we should respond to a similar widespread outbreak of biological disease and provide data on the long-term effects of the flu on a pregnant woman.


Sheingold, B. H., Hahn, J. A. (2014). The history of healthcare quality: The first 100 years 1860- 1960. International Journal of Africa Nursing Sciences. Vol. 1. Pages 18 – 22. DOI: https://doi.org/10.1016/j.ijans.2014.05.002

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