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Demographic Analysis of Zip Code 82934: A Study of Low Diversity and Racial Composition
CATEGORY
Demographics
DATA
Population
Median Income
Racial Distributions
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Demographics
Population
Median Income
Racial Distributions
Zip code 82934, located in Granger, Wyoming, exhibits a unique demographic profile characterized by an extremely small population. As of 2022, the area is classified as having "Low Diversity" with a population of one person, identified as white. The median income for this sole resident was $40,151 in 2022, which is below the national median income.
Over the past decade, this zip code has maintained a "Low Diversity" classification, with the white population representing either 100% or 50% of the total population, depending on the year. The population fluctuated between 1 and 2 individuals throughout the period, limiting the ability to draw meaningful conclusions about demographic shifts.
The median income in this area has shown volatility over the years. From a peak of $79,687 in 2016, it has generally decreased to $40,151 in 2022. This represents a decrease of nearly 50% over six years. Given the minimal population size, these changes may reflect individual circumstances rather than broader economic trends.
The demographic and economic situation in this zip code is atypical and not representative of broader trends. Most communities, even in rural areas, have larger populations that allow for more meaningful analysis of diversity and economic patterns. The population density of approximately 0.4 people per square mile is below the national average and typical rural densities.
With such a small population, any change in individual circumstances can significantly alter the statistical profile of the area. This makes it difficult to draw broader conclusions or identify trends that might be applicable to larger communities or regions.
In conclusion, while this zip code can be categorized as having "Low Diversity" with notable income fluctuations, the extremely small population size limits the applicability of these observations to wider demographic or economic analyses. This case demonstrates the limitations of statistical analysis when applied to extremely small populations.
