Descriptive Statistics Calculation

There is often a requirement to evaluate descriptive statistics for data within an organization or for health care information. Every year, the National Cancer Institute collects and publishes data based on patient demographics. Understanding differences between the groups based upon the collected data often informs health care professionals about research, treatment options, or patient education.

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 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 are calculated, provide a 150-250-word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups.

APA style is not required, but solid academic writing is expected.

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American Association of Colleges of Nursing Core Competencies for Professional Nursing Education

This assignment aligns to AACN Core Competencies 7.3 

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Descriptive Statistics Calculation

Title: Evaluating Descriptive Statistics in Healthcare Data Analysis

Introduction

The collection and analysis of healthcare data play a crucial role in informing healthcare professionals, researchers, and policymakers about the current state of health within a population. The National Cancer Institute (NCI) annually collects and publishes data based on patient demographics, providing valuable insights into the prevalence and outcomes of cancer among different racial and ethnic groups. In this essay, we will explore the importance of evaluating descriptive statistics in healthcare data analysis, specifically focusing on the NCI’s data spreadsheet, which contains information about various racial and ethnic groups.

Descriptive Statistics Calculation

To gain a comprehensive understanding of the data, we calculate several key descriptive statistics for each race/ethnicity group:

  1. Measures of Central Tendency:
    • Mean: This statistic represents the average value of a variable within each group, providing insight into the typical value. It helps identify the central point around which data points tend to cluster.
    • Median: The median is the middle value when data is ordered from smallest to largest. It is a robust measure of central tendency that helps mitigate the impact of extreme values.
    • Mode: The mode is the most frequently occurring value in the dataset, giving us insight into the most common value within each group.
  2. Measures of Variation:
    • Variance: Variance measures the spread or dispersion of data points within each group. It quantifies how much individual data points deviate from the mean.
    • Standard Deviation: Standard deviation is the square root of the variance and provides a more interpretable measure of data spread.
    • Range: While the formula for range is not needed, it is still a useful measure of variation as it simply represents the difference between the highest and lowest values in a dataset.

Analysis of Descriptive Statistics

Analyzing the descriptive statistics for the NCI’s data on race/ethnicity groups can help uncover important differences and health outcomes:

  1. Central Tendency: Understanding the mean, median, and mode for each group allows us to identify which racial and ethnic groups have higher or lower cancer incidence rates. Differences in central tendencies may indicate disparities in healthcare access, genetics, or lifestyle factors contributing to cancer risk.
  2. Variation: Variance and standard deviation inform us about the spread of data within each group. Higher variance and standard deviation suggest greater variability in cancer outcomes. These variations may prompt further investigation into factors contributing to disparities in healthcare outcomes.
  3. Range: Although range is a simple measure, it highlights the gap between the highest and lowest values. Examining the range can reveal the extent of differences in cancer incidence or outcomes between groups.

In conclusion, evaluating descriptive statistics is a crucial step in healthcare data analysis. It helps healthcare professionals and researchers identify disparities, make informed decisions, and tailor interventions to improve health outcomes. The NCI’s data on race/ethnicity groups is a valuable resource that can contribute to our understanding of cancer disparities and inform strategies for better healthcare delivery and patient education.

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