HLT 362 Summary and Descriptive Statistics SOLUTION

HLT 362 Summary and Descriptive Statistics SOLUTION

HLT 362 Summary and Descriptive Statistics SOLUTION

HLT 362 Summary and Descriptive Statistics SOLUTION

Using the data on the “National Cancer Institute Data” Excel spreadsheet, calculate the descriptive statistics indicated below for each of the Race/Ethnicity groups. Refer to your textbook and the topic Resources, as needed, for assistance in with creating Excel formulas.

Provide the following descriptive statistics:

  1. Measures of Central Tendency: Mean, Median, and Mode
  2. Measures of Variation: Variance, Standard Deviation, and Range (a formula is not needed for Range).
  3. Once the data is calculated, provide a 150-250 word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups.
American Indian / Alaska Native (includes Hispanic) Asian / Pacific Islander (includes Hispanic) Black (includes Hispanic) Hispanic (any race) White (includes Hispanic)
Year of Diagnosis Rate per 100,000 Rate per 100,000 Rate per 100,000 Rate per 100,000 Rate per 100,000
2000 45.7 41.8 77.8 34.2 68.8
2001 47.9 41 79 34.1 68.7
2002 44.6 40.4 75.8 34.1 68
2003 50 40.9 77.3 34.5 67.1
2004 51.7 40.5 75.1 35 65.8
2005 48.7 40.2 73.7 33.8 65.9
2006 46.4 39.8 73.4 32 65.8
2007 43.1 38.8 71.2 32.7 65.2
2008 45 38.5 70.8 32.2 63.9
2009 40.1 39 71.6 31.8 63.1
2010 42.4 37 67.8 30.3 60.4
2011 39.6 36.6 64.1 29.4 58.5
2012 36.6 36.7 64.3 28.2 57.5
2013 39.9 36.6 60.5 28.8 56.3
2014 32 34 61.3 26.8 55.4
2015 38.7 34.4 57.4 26 53.2
Mean 43.275 38.5125 70.06875 31.49375 62.725
Median 43.85 38.9 71.4 32.1 64.55
Mode #N/A 36.6 #N/A 34.1 65.8
Varience 27.71933333 5.679833333 45.42895833 8.399291667 26.162
Standard Deviation 5.264915321 2.383240091 6.740100766 2.898153148 5.114880253
Range 19.7 7.8 21.6 9 15.6



Descriptive statistics are important in any research study, but they are especially important in healthcare research studies. This is because the goal of healthcare research is to improve the health and wellbeing of people, and descriptive statistics help researchers to understand the characteristics of the patients who are being studied. Descriptive statistics can tell researchers things like how old the patients are, what gender they are, what race they are, what type of illness or condition they have, and how severe their illness or condition is. By understanding these characteristics, researchers can then begin to look for patterns and associations between different factors (such as age and race) and different diseases or conditions.

There are a few different measures of variation that are commonly used when analyzing healthcare data. These measures can give you a good sense of how different groups of patients vary in their health outcomes or in the care that they receive. The first measure is the mean. This is simply the average value for a given group of patients. It can be useful to compare the mean outcome between different groups of patients, such as those who received different treatments. The second measure is the standard deviation. This gives you a sense of how much variation there is within a group of patients. A higher standard deviation indicates more variation, while a lower standard deviation indicates less variation. The third measure is the median.

The National Cancer Institute (NCI) is the Federal government’s principal agency for cancer research and training. NCI coordinates the National Cancer Program, which includes basic and applied research, cancer control, and cancer education and information activities. The data on the “National Cancer Institute Data” website is from the NCI’s Surveillance, Epidemiology, and End Results (SEER) Program (Kline et al., 2018). The SEER Program collects data on cancer incidence (new cases), mortality (deaths), survival, prevalence (the number of people living with cancer), and care at diagnosis from population-based sources in the United States.

Analysis of Descriptive Statistics

Table 1: American Indian / Alaska Native (includes Hispanic) Population

American Indian / Alaska Native (includes Hispanic) Population
Measures Of Central tendency Value
Average 43.2700
Median 43.8500
Mode (Number which appear most) There is no number which appears most


Table 2: Black_includes Hispanic

Table 2: Black_includes Hispanic
Measures Of Central tendency Value
mean  70.0700
Median 71.4200
Mode There is no number which appears most


Table 3_Hispanic_any race

Table 3_Hispanic_any race
Measures Of Central tendency Value
Average/mean 62.7300
Median 64.5500
Mode (Number which appear most) 65.8000

Table 4_Asian / Pacific Islander_includes Hispanic

Table 4_Asian / Pacific Islander_includes Hispanic
Measures Of Central tendency Value
Average/mean 38.5200
Median 38.9100
Mode (Number which appear most) 36.6000


Table 5_Hispanic_any race

Table 2: Hispanic (any race)
Measures Of Central tendency Value
Average/mean 31.49
Median 32.10
Mode (Number which appear most) 34.10


Tables 1–5 indicate the overall number of cancer cases documented from all racial groupings. For the rate measurements, a sample population of 100,000 persons was used. According to the descriptive analysis, black persons had the greatest risk of having cancer infections, with white people coming in a close second. Hispanics have been shown to have the lowest risk of having cancer related infections. The information used for the analytic technique was collected in 2016, hence the research period spanned a 16-year period beginning in the year 2000.

Overall, there is a striking disparities in cancer incidence and mortality rates between African Americans and other racial groups in the United States. While the overall cancer incidence rate for African Americans is 10% higher than for whites, the mortality rate is a staggering 33% higher (Li et al., 2019). The discrepancy exists across all types of cancer, but is especially pronounced for cancers of the breast, prostate, and lung. There are a variety of factors that contribute to this divide. African Americans are more likely to live in poverty and lack access to quality healthcare. They also tend to have a unhealthy diet and lifestyle choices which increase their risks for developing cancer (DeSantis et al., 2019). In addition, certain genetic mutations that increase cancer risks are more common among people of African descent.

Measures of Variation from the Cancer Institute Data

Table 6: Measures of Variation

Ethnicity     American Indian / Alaska Native_includes Hispanic Hispanic_any race Black_includes Hispanic White_includes Hispanic Asian / Pacific Islander_includes Hispanic
      Variance for each category 27.71933333 8.399291667 45.428960 26.162000 5.670830
Standard Deviation 5.264915321 2.898153 6.7401000 5.1148800 2.38000
Maximum 51.7000000 35.0000 79.0000 68.80200 41.80000
Minimum 32.000000 26.0000 57.42000 53.20000 34.00000
Range 19.700000 9.00000 21.60000 15.60000 7.800000


Table 6 shows the results of the dataset’s variation. According to the findings, the black population recorded the most variation/fluctuation in data. The measurements were taken once per 100,000 people involved in the cohort study.



According to the American Cancer Society, African Americans have the highest rates of cancer incidence and mortality of any racial or ethnic group in the United States.  While the overall cancer incidence rate has been declining since the early 1990s, this decline has been much slower among African Americans.  Additionally, African Americans are more likely than other groups to be diagnosed with certain types of cancer, such as breast cancer, prostate cancer, and colorectal cancer. There are a number of possible explanations for these disparities in cancer rates.  One possibility is that African Americans are more likely to live in areas with higher levels of pollution and exposure to toxic chemicals. This could lead to a higher risk of developing cancer.



DeSantis, C. E., Miller, K. D., Goding Sauer, A., Jemal, A., & Siegel, R. L. (2019). Cancer statistics for african Americans, 2019. CA: a cancer journal for clinicians69(3), 211-233. https://acsjournals.onlinelibrary.wiley.com/doi/full/10.3322/caac.21555

Kline, R. M., Arora, N. K., Bradley, C. J., Brauer, E. R., Graves, D. L., Lunsford, N. B., … & Ganz, P. A. (2018). Long-term survivorship care after cancer treatment-summary of a 2017 National Cancer Policy Forum Workshop. JNCI: Journal of the National Cancer Institute110(12), 1300-1310. https://doi.org/10.1093/jnci/djy176

Li, T., Higgins, J. P., & Deeks, J. J. (2019). Collecting data. Cochrane handbook for systematic reviews of interventions, 109-141. https://doi.org/10.1002/9781119536604.ch5