About this dataset

Context

The dataset tabulates the Pullman population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Pullman across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Pullman was 32,863, a 1.23% increase year-by-year from 2022. Previously, in 2022, Pullman population was 32,465, an increase of 15.24% compared to a population of 28,171 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Pullman increased by 7,842. In this period, the peak population was 34,523 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Pullman is shown in this column.
• Year on Year Change: This column displays the change in Pullman population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Pullman Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Pullman by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Pullman across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.99% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Pullman is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Pullman total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Pullman Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Pullman population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Pullman. The dataset can be utilized to understand the population distribution of Pullman by age. For example, using this dataset, we can identify the largest age group in Pullman.

Key observations

The largest age group in Pullman, WA was for the group of age 20 to 24 years years with a population of 10,351 (32.41%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Pullman, WA was the 80 to 84 years years with a population of 184 (0.58%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Pullman is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Pullman total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Pullman Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Pullman by race. It includes the population of Pullman across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Pullman across relevant racial categories.

Key observations

The percent distribution of Pullman population by race (across all racial categories recognized by the U.S. Census Bureau): 71.28% are white, 1.91% are Black or African American, 0.80% are American Indian and Alaska Native, 10.65% are Asian, 0.26% are Native Hawaiian and other Pacific Islander, 2.65% are some other race and 12.45% are multiracial.

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: This column displays the racial categories (excluding ethnicity) for the Pullman
• Population: The population of the racial category (excluding ethnicity) in the Pullman is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Pullman total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Pullman Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Pullman, WA population pyramid, which represents the Pullman population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Pullman, WA, is 12.4.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Pullman, WA, is 7.8.
• Total dependency ratio for Pullman, WA is 20.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Pullman, WA is 12.9.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Pullman population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Pullman for the selected age group is shown in the following column.
• Population (Female): The female population in the Pullman for the selected age group is shown in the following column.
• Total Population: The total population of the Pullman for the selected age group is shown in the following column.

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 Pullman Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Pullman by race. It includes the distribution of the Non-Hispanic population of Pullman across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Pullman across relevant racial categories.

Key observations

Of the Non-Hispanic population in Pullman, the largest racial group is White alone with a population of 21,584 (74.75% of the total Non-Hispanic population).

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: This column displays the racial categories (for Non-Hispanic) for the Pullman
• Population: The population of the racial category (for Non-Hispanic) in the Pullman is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Pullman total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Pullman Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Pullman Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Pullman, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Pullman.

Key observations

Among the Hispanic population in Pullman, regardless of the race, the largest group is of Mexican origin, with a population of 2,077 (67.77% of the total Hispanic population).

Content

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

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the Pullman
• Population: The population of the specific origin for Hispanic or Latino population in the Pullman is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Pullman total Hispanic or Latino population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Pullman Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Pullman population by year. The dataset can be utilized to understand the population trend of Pullman.

Content

The dataset constitues the following datasets

• Pullman, WA Population Dataset: Yearly Figures, Population Change, and Percent Change Analysis

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/.

About this dataset

Context

The dataset tabulates the Pullman population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Pullman.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Pullman, WA Population Breakdown by Race
• Pullman, WA Non-Hispanic Population Breakdown by Race
• Pullman, WA Hispanic or Latino Population Distribution by Their Ancestries

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/.

About this dataset

Context

The dataset tabulates the Pullman median household income by race. The dataset can be utilized to understand the racial distribution of Pullman income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Pullman, WA median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Pullman, WA (2021, in 2022 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Pullman median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the Pullman household income by gender. The dataset can be utilized to understand the gender-based income distribution of Pullman income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Pullman, WA annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Pullman, WA annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Pullman income distribution by gender. You can refer the same here

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Pullman, WA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 5,374, while the mean income for the highest quintile (20% of households with the highest income) is 206,137. This indicates that the top earners earn 38 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 342,048, which is 165.93% higher compared to the highest quintile, and 6364.87% higher compared to the lowest quintile.

Content

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

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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 Pullman median household income. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Pullman. 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 Pullman population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 71.28% of the total residents in Pullman. Notably, the median household income for White households is $47,231. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $49,223. This reveals that, while Whites may be the most numerous in Pullman, Two or More Races 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 Pullman.
• 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 Pullman median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Pullman, WA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 4,140, while the mean income for the highest quintile (20% of households with the highest income) is 200,508. This indicates that the top earners earn 48 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 361,582, which is 180.33% higher compared to the highest quintile, and 8733.86% higher compared to the lowest quintile.

https://i.neilsberg.com/ch/pullman-wa-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in Pullman, WA (in 2022 inflation-adjusted dollars))">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

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 Pullman median household income. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Pullman. The dataset can be utilized to gain insights into gender-based income distribution within the Pullman population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Pullman, among individuals aged 15 years and older with income, there were 12,663 men and 11,847 women in the workforce. Among them, 4,776 men were engaged in full-time, year-round employment, while 3,093 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 11.33% fell within the income range of under $24,999, while 14.84% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 27.68% of men in full-time roles earned incomes exceeding $100,000, while 13.39% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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

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Recommended for further research

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

Data reported in research published in Crop Science, “Mapping the quantitative field resistance to stripe rust in a hard winter wheat population ‘Overley’ × ‘Overland.’” Authors are Wardah Mustahsan, Mary J. Guttieri, Robert L. Bowden, Kimberley Garland-Campbell, Katherine Jordan, Guihua Bai, Guorong Zhang from USDA Agricultural Research Service and Kansas State University. This study was conducted to identify quantitative trait loci (QTL) associated with field resistance to stripe rust, also known as yellow rust (YR), in hard winter wheat. Stripe rust infection type and severity were rated in recombinant inbred lines (RILs, n=204) derived from a cross between hard red winter wheat cultivars ‘Overley’ and ‘Overland’ in replicated field trials in the Great Plains and Pacific Northwest. RILs (n=184) were genotyped with reduced representation sequencing to produce SNP markers from alignment to the ‘Chinese Spring’ reference sequence, IWGSC v2.1, and from alignment to the reference sequence for ‘Jagger’, which is a parent of Overley. Genetic linkage maps were developed independently from each set of SNP markers. QTL analysis identified genomic regions on chromosome arms 2AS, 2BS, 2BL, and 2DL that were associated with stripe rust resistance using multi-environment best linear unbiased predictors for stripe rust infection type and severity. Results for the two linkage maps were very similar. PCR-based SNP marker assays associated with the QTL regions were developed to efficiently identify these genomic regions in breeding populations.Field response to YR was evaluated in seven trials: Rossville, KS (2018 and 2019), Hays, KS (2019), Pullman, WA (2019 and 2020) and Central Ferry, WA (2019 and 2020). An augmented experimental design was used at Rossville, KS with highly replicated checks and two full replications of RILs (n=187 in 2018; n=204 in 2019). The field experiment at Hays was arranged in a partially replicated augmented design with one or two replications of each RIL (n=194). The parental checks (Overley and Overland) were represented in three blocks for each of the two field replications at Hays, and RILs were distributed among blocks; not all RILs were present in each replication. RILs were arranged in an augmented design with two replications at Pullman (n=204 RILs) and Central Ferry (n=155 RILs in 2019; n=204 in 2020). At Pullman and Central Ferry.The trials at Rossville, KS were inoculated using an inoculum consisting of equal parts of four isolates that were all virulent to Yr9. Two isolates were collected in Kansas in 2010 and had virulence to Yr17 but not QYr.tamu-2B. The other two isolates were from Kansas in 2012 and had virulence to QYr.tamu-2B, but not Yr17. Susceptible spreader rows (KS89180B, carrying Yr9) were inoculated several times during the tillering stage in the evenings with an ultra-low volume sprayer using a suspension of 2 mL of fresh urediniospores in 1 L of Soltrol 170 isoparaffin oil. Trials at Pullman, WA and Central Ferry, WA were evaluated under natural inoculum supplemented by a mixture of isolates collected in the previous field season. The trial at Hays, KS was evaluated under natural infection.Data collection at Rossville, KS began once the susceptible check (KS89180B) had an infection severity coverage of ~10% and continued until senescence. In Rossville, disease ratings (IT and SEV) were collected on 16, 22, and 28th of May 2019. Most ratings in Rossville were taken some time after heading from Zadoks stages 55 to 70. In Pullman, disease ratings were collected on July 1 and 12. In Central Ferry, disease ratings were taken on 12th and 18th of June 2019. The second rating date was used for subsequent statistical analysis. In Hays, disease ratings were taken on June 1, 2019, when the plants were in early booting or heading stages (Zadoks 31-41). Stripe rust evaluations were measured using two disease rating scales: IT (0-9; from no infection to highly susceptible, Line and Qayoum, 1992) and SEV based on visual estimation of the percent flag leaf area affected by the pathogen including associated chlorosis and necrosis (0-100%).DNA was extracted from seedlings, and genotyping-by-sequencing was conducted as described previously (Guttieri, 2020) on a subset of 189 lines (187 RILS and 2 parents) of which 23 RILs were F6-derived and 164 RILs were F9-derived. Single nucleotide polymorphisms (SNPs) were identified in parallel using reference-based calling in the TASSEL pipeline (Bradbury et al., 2007) using both the IWGSC v2.1 reference genome (Zhu et al., 2021) and the Jagger reference sequence (Wheat Genomes Project (http://www.10wheatgenomes.com/10-wheat-genomes-project-and-the-wheat-initiative/). The TASSEL pipeline was executed with the following parameters: minimum read count = 1, minimum quality score = 0, minimum locus coverage = 0.19, and minimum minor allele frequency = 0.005, minimum heterozygous proportion = 0, and removal of minor SNP states. The resulting SNP datasets from each reference sequence were filtered in TASSEL by taxa (RILs) and sites (SNPs). The RILs were filtered to include those RILs for which at least 20% sites were present. The sites were filtered to include sites for which > 60% of RILs were called, minor allele frequency (MAF) > 0.25, maximum allele frequency < 0.75, maximum heterozygous proportion = 0.25, and removal of minor SNP states. The ABH plugin in TASSEL was applied to this reduced dataset to identify parental genotypes.Resources in this dataset:Resource Title: Multilocation Stripe Rust Data File Name: MultiLocRawData_Yr.xslxResource Title: OvOv_CS_TasselSNPCalls File Name: KSM17-OvOv-parentsmerge1.hmp.txt Resource Description: Output of TASSEL GBS SNP calling pipeline using Chinese Spring v2 refseq. Starting point for map construction pipeline.Resource Title: OvOv GBS SNP Calls Jagger RefSeq File Name: KSM17-OvOv-Jaggerpmerge1.hmp.txt Resource Description: TASSEL output from reference-based SNP calling using the Jagger reference sequenceResource Title: QTL-Associated KASP Markers with IT and SEV BLUPs File Name: KASP_Data_IT_SEV.xlsx Resource Description: Multilocation best linear unbiased predictors (BLUPs) for stripe rust infection type and severity of recombinant inbred lines. KASP assay results for QTL-associated SNPs, coded Overley = 2, Overland = 0, Het = 1, Missing = "."