Summary And Descriptive Statistics For Students' Names And I ✓ Solved

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Summary and Descriptive Statistics

Measures of Central Tendency

The measures of central tendency include the mean, the mode, and the median. They describe the center point of a data set (Aldous, 2016). For this data, we calculate the measures of central tendency for the race/ethnic groups. We use the AVERAGE, MEDIAN, and MODE functions in Excel to calculate the mean, median, and mode, respectively. The following is a summary for the measures:

  • American Indian / Alaska Native (includes Hispanic): Mean 43.725, Median 43.55, Mode N/A
  • Asian / Pacific Islander (includes Hispanic): Mean 36.6, Median N/A, Mode 36.6
  • Black (includes Hispanic): Mean 34.8, Median 34.8, Mode N/A
  • Hispanic (any race): Mean 34.1, Median N/A, Mode 34.1
  • White (includes Hispanic): Mean 65.8, Median N/A, Mode 65.8

From the above table, Black (includes Hispanic) has the highest mean rate per 100,000 among the ethnic groups while Hispanic (any race) has the lowest mean rate per 100,000. Similarly, Black (includes Hispanic) has the highest median rate per 100,000 among the ethnic groups while Hispanic (any race) has the lowest mean rate per 100,000. American Indian / Alaska Native (includes Hispanic) and Black (includes Hispanic) do not have a mode, while the modes for Asian / Pacific Islander (includes Hispanic), Hispanic (any race), and White (includes Hispanic) are 36.6, 34.1, and 65.8, respectively.

Measures of Dispersion

They include the variance, the standard deviation, and the range. They measure how the data is spread (Aldous, 2016). In this case, we measure the sample values assuming the data is a sample. The summary is:

  • American Indian / Alaska Native (includes Hispanic): Sample Variance 27.162
  • Asian / Pacific Islander (includes Hispanic): Sample Standard deviation 5. Range 19.6
  • Black (includes Hispanic): highest variance, standard deviation, and range
  • Hispanic (any race): lowest variance, standard deviation, and range

This shows that Blacks (includes Hispanic) have the largest spread of the rates per 100,000 while Asian / Pacific Islander (includes Hispanic) have the smallest spread of the rates per 100,000.

References

Aldous, D.J. (2016). Descriptive Statistics. New Rochelle, N.Y: Magnum Publishing.

Paper For Above Instructions

The statistical analysis of data regarding race and ethnic groups is imperative for understanding disparities in various aspects of society, including healthcare outcomes and educational achievements. One of the fundamental statistical explorations involves both summary statistics and measures of central tendency, which provide insight into how data from different racial and ethnic groups are distributed and understood.

Measures of central tendency, specifically the mean, median, and mode, allow for a potential understanding of differences across various ethnicities. The mean provides an average value of the dataset, giving an overall sense of the data's central point. Meanwhile, the median gives insight into the middle point of the data distribution, especially beneficial when outliers are present, while the mode indicates the most frequently occurring value within the dataset. In the current analysis, we find that the Black (includes Hispanic) group exhibited the highest mean and median rates per 100,000 individuals, indicative of potentially higher occurrences of the measured statistic within this population.

In contrast, the Hispanic (any race) group illustrates the lowest mean and median rates, emphasizing the need to assess socioeconomic and health-related factors that may lead to a lower rate among this demographic. The evident lack of a mode in several of the ethnic categories, particularly for American Indian / Alaska Native and Black groups, indicates diversity in the data points, failing to yield a distinct frequent occurrence. Thus, understanding these statistics is crucial for healthcare professionals to create equitable healthcare strategies that address these variations.

Moving beyond central tendencies, measures of dispersion such as variance, standard deviation, and range play vital roles in elucidating the data spread. The variance quantifies how much the numbers vary from the mean, while standard deviation provides a measure of the average distance of each data point from the mean. In this analysis, it was found that the Black (includes Hispanic) group has the highest variance and standard deviation, indicating that outcomes are spread over a broader range than for the Asian / Pacific Islander group, who showed the least variations. This observation suggests that while some populations may frequently experience specific rates per 100,000 individuals, others may display wide variability, which must be recognized to better inform public health strategies.

Further analysis into typical healthcare metrics can unveil underlying issues linked to race and ethnicity. For instance, studies indicating disproportionate healthcare access among racial groups directly impact these statistics. Previous data has demonstrated that access to adequate health care correlates strongly with socioeconomic status, which varies significantly by race and ethnicity (Williams & Mohammed, 2009). Therefore, it is critical to view descriptive statistics within the context of broader social determinants that encompass factors such as health insurance rates, income inequality, education, and systemic bias.

Outcomes derived from the analysis of these descriptive statistics indicate the potential for bias, segregation, or systemic inequities against specific racial and ethnic populations. The increased mean and median observed for Black individuals might suggest a significant area in which healthcare professionals should prioritize interventions and community engagement initiatives to address the discrepancies, thus contributing to a more precise understanding of public health needs.

Moreover, ethical considerations must always be at the forefront of research and statistics in this field. Research ethics necessitate a commitment to integrity and moral obligations to avoid misrepresentation or misleading conclusions derived from data manipulations. When examining racial data, researchers should prioritize transparency in presenting findings and emphasize ensuring that their work does not contribute to racial discrimination or stigmatization (National Institutes of Health, 2003).

In summary, while descriptive statistics provide a robust framework for analyzing data concerning race and ethnicity, their implications should always be interpreted within the context of associated socioeconomic factors and ethical responsibility. Healthcare professionals must leverage these insights to identify systemic inequities that persist within society and work towards implementing effective interventions and programs aimed at mitigating disparities.

References

  • Aldous, D.J. (2016). Descriptive Statistics. New Rochelle, N.Y: Magnum Publishing.
  • Williams, D.R., & Mohammed, S.A. (2009). Discrimination and racial disparities in health: evidence and needed research. Journal of Behavioral Medicine, 32(1), 20-47.
  • National Institutes of Health. (2003). Protecting Participants in Research: Ethical Considerations in Initiating a Research Protocol.
  • American Psychological Association. (2019). Publication manual of the American Psychological Association (7th ed.). Washington, DC: Author.
  • Krieger, N. (2012). Methods for social epidemiology. In: Social Epidemiology (pp. 17-30). Oxford University Press.
  • Smedley, B.D., Stith, A.Y., & Nelson, A.R. (2003). Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. National Academies Press.
  • Phelan, J.C., & Link, B.G. (2015). Is racism a fundamental cause of inequalities in health? Annual Review of Sociology, 41, 75-86.
  • Fiscella, K., & Williams, D.R. (2004). Health disparities based on socioeconomic inequities: implications for multiculturalism. Journal of Health Communication, 9(Suppl), 63-90.
  • Hoffman, K.A., et al. (2018). Evolving Ethical Perspectives in Nursing Research. Nursing Ethics, 25(7), 835-844.
  • United States Department of Health and Human Services. (2016). Health Equity Strategy.

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