About this dataset

Context

The dataset presents the median household income across different racial categories in Tucson. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Tucson population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 58.17% of the total residents in Tucson. Notably, the median household income for White households is $56,907. Interestingly, despite the White population being the most populous, it is worth noting that Native Hawaiian and Other Pacific Islander households actually reports the highest median household income, with a median income of $58,431. This reveals that, while Whites may be the most numerous in Tucson, Native Hawaiian and Other Pacific Islander households experience greater economic prosperity in terms of median household income.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Tucson.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Tucson median household income by race. You can refer the same here

This dataset contains Community Statistical Areas (CSAs) boundaries created by the Arizona Department of Health Services to represent Arizona communities while maintaining population numbers sufficient for statistical analysis. Using census tracts as the base geography, CSAs are updated every Census using a repeatable rule based methodology intended to preserve community boundaries, provide population numbers conducive to statistical analysis, and account for demographic variation.Summary:139 Community Statistical Areas56 in metro Phoenix area20 in metro Tucson areaPopulations of 10,000-200,000 (except tribal areas)Areas no greater than 7,500 square miles (except tribal areas)Reflect existing communities, including cities, towns, municipal planning areas (i.e. City of Phoenix Villages), and Tribal lands (reservations) A crosswalk between Census 2020 Tracts and CSAs is available here.Update Frequency: Every 10 Years (Decennial census)

This dataset contains Community Statistical Areas (CSAs) boundaries created by the Arizona Department of Health Services to represent Arizona communities while maintaining population numbers sufficient for statistical analysis. Using census tracts as the base geography, CSAs are updated every Census using a repeatable rule based methodology intended to preserve community boundaries, provide population numbers conducive to statistical analysis, and account for demographic variation.Summary:139 Community Statistical Areas56 in metro Phoenix area20 in metro Tucson areaPopulations of 10,000-200,000 (except tribal areas)Areas no greater than 7,500 square miles (except tribal areas)Reflect existing communities, including cities, towns, municipal planning areas (i.e. City of Phoenix Villages), and Tribal lands (reservations) A crosswalk between Census 2020 Tracts and CSAs is available here.Update Frequency: Every 10 Years (Decennial census)

AbstractArctic sea ice extent (SIE) is declining at an accelerating rate with a wide range of ecological consequences. However, determining sea ice effects on tundra vegetation remains a challenge. In this study, we examined the universality or lack thereof in tundra shrub growth responses to changes in SIE and summer climate across the Pan-Arctic, taking advantage of 23 tundra shrub-ring chronologies from 19 widely distributed sites (56⁰-83⁰N). MethodsWe acquired both published and unpublished deciduous shrub-ring chronologies that were distributed throughout the Arctic region and covered, if possible, the entire 40 year-long period of passive microwave satellite-based estimates of arctic sea ice extent (SIE) (1979-present). In order to perform a comparable study at the biome level, our synthesis focused on two shrub genera of commonly studied and widespread deciduous shrubs: Betula and Salix. Shrub-ring data were included in our analyses if the corresponding chronologies i) covered the common period (1979-2008) and ii) had an EPS (a theoretical indicator of how well the chronology represents the population mean) greater than 0.75. Our final dataset consisted of 23 chronologies (9 Betula spp. chronologies and 14 Salix spp. chronologies), 641 shrubs (306 Betula shrubs and 335 Salix shrubs), and 753 cross-sections. This dataset consists of 23 RWL files for 23 shrub ring chronologies. Each RWL file (Tucson format, unit = mm, resolution 0.001) contains raw data for all individual shrub growth series used to established each site chronology. Raw data are averaged at the plant level for the shrubs that were subjected to serial sectioning or when more than one cross-section was sampled per individual shrub. These are raw individual shrub data, not detrended or standardized. Usage notesReadMe_v01: File description for manuscript Buchwal et al. 2020: Divergence of Arctic shrub growth associated with sea ice decline. https://www.pnas.org/content/early/2020/12/09/2013311117 Version_01 Date: November 22, 2020 Contact person: Agata Buchwal, Adam Mickiewicz University Poznan, Poland, ORCID ID: 0000-0001-6879-6656; kamzik@amu.edu.pl This repository consist of: #1: Table 1: Metadata file for 23 shrub ring chronologies used in the Buchwal et al. (2020) synthesis #2: 23 RWL files for 23 shrub ring chronologies. Each RWL file (Tucson format, unit = mm, resolution 0.001) contains raw data for all individual shrub growth series used to established each site chronology. Raw data are averaged at the plant level for the shrubs that were subjected to serial sectioning or when more than one cross-section was sampled per individual shrub. These data are not detrended or standardized. If You need shrub ring data at the cross-sectional level, please contact a relevant data contributor/-s (Table 1, column Q). In order to open RWL files (.rwl) you can use ‘read.rwl’ function in dplR package (Bunn 2008) in R (R Core Team). List of RWL files attached: AF_SAR.rwl BL_BGL.rwl BS_BGL.rwl BT_BGL.rwl DE_SGL.rwl DK_BNA.rwl EB_SPO.rwl GR_BGL.rwl HE_SAR.rwl HE_SRI.rwl KG_BNA.rwl KG_SGL.rwl KY_BNA.rwl KY_SPU.rwl LA_SAR.rwl LB_SRI.rwl PL_SAR.rwl RE_SAR.rwl TL_BNA.rwl UM_BGL.rwl VA_SRI.rwl YR_SRI.rwl ZA_SAR.rwl References: A. G. Bunn, A dendrochronology program library in R (dplR). Dendrochronologia 26, 115-124 (2008). R Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.URL https://www.R-project.org/ (2018).

Primary Care Areas (PCAs) are geographic regions created by the Arizona Department of Health Services (ADHS). They are designed to represent the communities of the state while maintaining populations conducive to statistical/spatial analysis. PCAs are built from US Census Tracts and are updated every Census using a repeatable rule based methodology intended to preserve community boundaries, provide population numbers conducive to statistical analysis, account for demographic variation and represent common utilization of primary care services. The creation and maintenance of PCAs is required by Arizona Administrative Code R9-24-204 for use in designating Medically Underserved Areas. PCA Summary 126 AZ Primary Care Areas55 in metro Phoenix area20 in metro Tucson areaPopulations of 10,000-200,000 (except tribal areas)Areas no greater than 7,500 square miles (except tribal areas)Reflect existing communities, including cities, towns, municipal planning areas (i.e. City of Phoenix Villages), and Tribal lands (reservations)UPDATE FREQUENCY: Every Decennial Census/10 years