CRJ_575_CriticalThinkingModule1

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Variable Identification (Community in Another State) Colorado State University Global CRJ 575: Analytical Methods Dr. Koehle September 9, 2023 1

2 Variable Identification (Community in Another State) An essential tool used by the United States government to collect demographic, economic, social, and housing information across the country, the U.S. Census Bureau’s annual collection has a crucial role encompassing innumerable aspects of government operation, public policy, and decision-making. Responses by survey participants rely on information alongside the Decennial census when determining where important services are needed such as hospitals, schools, and highways in turn informing people how federal funds are annually distributed (US Census Bureau, 2023). The ACS collects information through four different methods; in-person interviews, the internet, mail, and telephone while the Decennial census is a population survey conducted every ten years by the United States Department of Commerce, Bureau of the Census. Through the utilization of the American Community Survey (ACS) and the Decennial census, the author will present a summary of various statistics in El Paso County, Colorado further providing statistics in the similarly sized county of Monroe, New York. The author will conclude whether the variables are nominal, ordinal, or interval/ratio-scale. Demographic Variables The total population in El Paso County, Colorado is 730,395 people (United States Census Bureau, 2020). In Monroe County, New York, the total population is 759,443. The Hispanic or Latino population is 129,984 which is 67.0% of the total population in El Paso County, Colorado while in Monroe County, New York, it is 72,745 or 9.6% of the population. Regarding race and Hispanic origin, in El Paso County, Colorado, for the variable White Alone, it is 82.6%, Black or African American at 6.9%, and Asian at 3.4%. In Monroe County, New York, the variable White Alone is 76%, Black or African American at 16.6%, and Asian at 3.9%. When looking at economic variables, the median household income in El Paso County, Colorado is $79,427 with Monroe County, New York being $65,957 (United States Census

3 Bureau, 2020). Statistical information for the employment rate in El Paso County, Colorado is 58.2%, and 59.8% in Monroe County, New York. Statistical information for persons in poverty shows that 9.6% of the population is in poverty in El Paso County, Colorado while the percentage of persons in poverty in Monroe County, New York is 13.3%. When examining sociodemographic variables, the percentage of persons aged 25 or older for the variable high school graduate or higher is 94.4% while in Monroe County, New York the percentage of persons aged 25 or older who have graduated high school or higher is 91.1% (United States Census Bureau, 2023). Upon further examination, the author discovered that individuals with a bachelor’s degree or higher in El Paso County, Colorado was 41.7% and the percentage of persons in Monroe County, New York with a bachelor’s degree or higher was 40.4%. When looking at the number of veterans residing in El Paso County, Colorado, there are 85,941, and in Monroe County, New York, 32,405. Measurement Scales Nominal variables in statistics are also referred to as categorical variables representing categories or groups without any inherent order or numerical value (Kaliyadan & Kulkarni, 2019). Used to classify data into distinct categories or labels, they are characteristically used to describe qualitative characteristics or attributes that are unable to be ranked or ordered in a meaningful way. Ordinal variables, categorical data in statistics, represent categories or labels with a meaningful order. While not having an inherent order like nominal variables, ordinal variables have categories that can be ordered or ranked in a meaningful way without the categories necessarily being uniform or equal (Gravel et al., 2020). Two types of quantitative data in statistics that provide more precise and informative measurements unlike ordinal or nominal variables are interval and ratio-scale variables (Podani et al., 2023). These continuous

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4 variables can take on a wider range of values within a defined range. While interval-scale variables lack a true zero point, ratio-scale variables possess a true zero point. Ratio-scale variables provide flexibility in conjunction with the most information for statistical analysis followed by interval-scale variables (Heavy, 2022). Nominal and ordinal variables are used for categorical data as equal intervals and ranking are not applicable. Regarding the statistical data provided for demographic variables the author acquired from the American Census Survey, both variable information included for the total population is interval/ratio-scale representing counts of individuals with meaningful differences while nominal variables are used for Hispanic or Latino population and race and Hispanic origin representing categories or groups of people with variables describing the racial and ethnic composition of the populations. The measurement scale used for the economic variables for the median household income variables is interval/ratio-scale as they represent income levels and about the employment rate, these too are interval/ratio-scale variables as they indicate the percentage of employed individuals. Persons in poverty is also an interval/ratio scale representing the percentage of the population living in poverty. Upon examination of the sociodemographic variables regarding those with a bachelor’s degree or higher, these are interval/ratio-scale as they represent a percentage of persons with a bachelor’s degree or higher with the same to be applied to high school graduates or higher. Regarding veterans, statistical data provided for both counties are interval/ratio-scale as they represent the number of veterans. Conclusion Exhibiting both similarities and differences in the demographic and economic profiles of El Paso County, Colorado, and Monroe County, New York, the author, after analysis of the

5 statistical data concludes that both counties have a relatively high educational attainment level, a higher percentage of persons in poverty in Monroe County, and a larger veteran population in El Paso County. The statistics provided are of importance for informed decision-making by researchers and policymakers as designed interventions and policies are implemented to meet the unique needs and characteristics of a city, county, or state.

6 References Gravel, N., Magdalou, B., & Moyes, P. (2020). Ranking distributions of an ordinal variable. Economic Theory , 71 (1). https://doi.org/10.1007/s00199-019-01241-4 Heavey, E. (2022). Statistics for nursing: A practical approach . Jones & Bartlett Learning. Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, descriptive statistics, and sample size. Indian Dermatology Online Journal , 10 (1). https://doi.org/10.4103/idoj.idoj_468_18 Podani, J., Schmera, D., & Bagella, S. (2023). Correlating variables with different scale types: A new framework based on matrix comparisons. Methods in Ecology and Evolution , 14 (4). https://doi.org/10.1111/2041-210x.14074 United States Census Bureau. (2023). 2021 ACS 1-year estimates . Census.gov. https://www.census.gov/programs-surveys/acs/technical-documentation/table-and- geography-changes/2021/1-year.html United States Census Bureau. (2020). U.S. census bureau quickfacts: El paso county, colorado . Census Bureau QuickFacts. https://www.census.gov/quickfacts/table/PST045215/08041 United States Census Bureau. (2023). The importance of the american community survey and the decennial census . Census.gov. https://www.census.gov/programs-surveys/acs/about/acs- and-census.html#:~:text=The%20American%20Community%20Survey,-Conducted %20every%20month&text=Provides%20current%20information%20to %20communities,understanding%20local%20issues%20and%20conditions. United States Department of Commerce. (2023). About commerce . U.S. Department of Commerce. https://www.commerce.gov/bureaus-and-offices/census

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