In 2024, the expected median starting salary for MBA graduates worldwide was ******* U.S. dollars. On the other hand, master's graduates in data analytics, business analytics, finance, and management were expected to have a median salary of ****** U.S. dollars.

United States PI: sa: Wage & Salary data was reported at 5,107.600 USD bn in Sep 2003. This records an increase from the previous number of 5,079.200 USD bn for Jun 2003. United States PI: sa: Wage & Salary data is updated quarterly, averaging 791.700 USD bn from Mar 1946 (Median) to Sep 2003, with 231 observations. The data reached an all-time high of 5,107.600 USD bn in Sep 2003 and a record low of 106.900 USD bn in Mar 1946. United States PI: sa: Wage & Salary data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A201: NIPA 1999: Personal Income and Disposition.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over (LEU0257856500A) from 2011 to 2023 about second quartile, occupation, benefits, compensation, jobs, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

In 2022, San Francisco had the highest median household income of cities ranking within the top 25 in terms of population, with a median household income in of 136,692 U.S. dollars. In that year, San Jose in California was ranked second, and Seattle, Washington third.

Following a fall after the great recession, median household income in the United States has been increasing in recent years. As of 2022, median household income by state was highest in Maryland, Washington, D.C., Utah, and Massachusetts. It was lowest in Mississippi, West Virginia, and Arkansas. Families with an annual income of 25,000 and 49,999 U.S. dollars made up the largest income bracket in America, with about 25.26 million households.

Data on median household income can be compared to statistics on personal income in the U.S. released by the Bureau of Economic Analysis. Personal income rose to around 21.8 trillion U.S. dollars in 2022, the highest value recorded. Personal income is a measure of the total income received by persons from all sources, while median household income is “the amount with divides the income distribution into two equal groups,” according to the U.S. Census Bureau. Half of the population in question lives above median income and half lives below. Though total personal income has increased in recent years, this wealth is not distributed throughout the population. In practical terms, income of most households has decreased. One additional statistic illustrates this disparity: for the lowest quintile of workers, mean household income has remained more or less steady for the past decade at about 13 to 16 thousand constant U.S. dollars annually. Meanwhile, income for the top five percent of workers has actually risen from about 285,000 U.S. dollars in 1990 to about 499,900 U.S. dollars in 2020.

United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over was 1252.00000 $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over reached a record high of 1252.00000 in January of 2023 and a record low of 893.00000 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over - last updated from the United States Federal Reserve on September of 2025.

United States PI: Wage & Salary data was reported at 5,125.346 USD bn in Oct 2003. This records an increase from the previous number of 5,116.011 USD bn for Sep 2003. United States PI: Wage & Salary data is updated monthly, averaging 1,506.368 USD bn from Jan 1959 (Median) to Oct 2003, with 538 observations. The data reached an all-time high of 5,125.346 USD bn in Oct 2003 and a record low of 252.183 USD bn in Jan 1959. United States PI: Wage & Salary data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A201: NIPA 1999: Personal Income and Disposition.

International Apple Pricing Strategy

Understanding Apple Product Prices in Relation to Local Salaries Worldwide

By [source]

About this dataset

This dataset offers a unique and powerful insight into the international markets of Apple products. It shows how Apple prices its products in different countries, and how those prices compare with average monthly salaries in those countries, giving a view on the affordability of these products. By looking at this data one can also get a better idea of what local markets look like around the world, as well as which countries may be better for price conscious shopping. All this data allows for deeper understanding of product pricing differences and potential spending power across regions to inform decisions by product or market makers about where to focus their efforts

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides an insight into Apple's international pricing strategies, which can be leveraged to draw conclusions about the company's approach to local markets around the world. To use this dataset, first look at how Apple prices its products in different countries by studying the columns 'price' and 'EUR Average Monthly Salary' and 'USD Average Monthly Salary'. Then examine how those prices compare with local salaries in those countries by comparing the columns 'EUR Average Monthly Salary' and 'USD Average Monthly Salary'. Finally, take a closer look at what types of products Apple offers in each location by studying columns such as 'sku', 'category', and ‘name’. By exploring these datasets you can gain insights into Apple's international pricing strategy while taking into account differences between local economies

Research Ideas

• Market segmentation: This dataset can provide valuable insights for companies looking to target different markets depending on the average local salary and purchasing power compared to Apple's current prices in that market.
• Price Optimization: Analyzing departments such as pricing, revenue management and strategic marketing could leverage this dataset develop smarter pricing strategies while also reflecting local income disparities as an integral factor​ in optimizing product prices across regions.
• Sales Planning & Budgeting: Companies can use this information to plan their annual budgets and forecast estimated sales performance across each of their markets according by benchmarking against Apple's current global prices for different products

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: average_monthly_salary_index.csv | Column name | Description | |:-------------------------------|:------------------------------------------------------------------| | Country | The country in which the data was collected. (String) | | EUR Average Monthly Salary | The average monthly salary in Euros for the country. (Float) | | USD Average Monthly Salary | The average monthly salary in US Dollars for the country. (Float) |

File: preus_mac_ipad_iphone.csv | Column name | Description | |:--------------|:----------------------------------------------------| | sku | Unique identifier for each product. (String) | | price | Price of the product in the local currency. (Float) | | category | Category of the product. (String) | | name | Name of the product. (String) | | country | Country where the product is sold. (String) | | store | Store where the product is sold. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

In March 2025, inflation amounted to 2.4 percent, while wages grew by 4.3 percent. The inflation rate has not exceeded the rate of wage growth since January 2023. Inflation in 2022 The high rates of inflation in 2022 meant that the real terms value of American wages took a hit. Many Americans report feelings of concern over the economy and a worsening of their financial situation. The inflation situation in the United States is one that was experienced globally in 2022, mainly due to COVID-19 related supply chain constraints and disruption due to the Russian invasion of Ukraine. The monthly inflation rate for the U.S. reached a 40-year high in June 2022 at 9.1 percent, and annual inflation for 2022 reached eight percent. Without appropriate wage increases, Americans will continue to see a decline in their purchasing power. Wages in the U.S. Despite the level of wage growth reaching 6.7 percent in the summer of 2022, it has not been enough to curb the impact of even higher inflation rates. The federally mandated minimum wage in the United States has not increased since 2009, meaning that individuals working minimum wage jobs have taken a real terms pay cut for the last twelve years. There are discrepancies between states - the minimum wage in California can be as high as 15.50 U.S. dollars per hour, while a business in Oklahoma may be as low as two U.S. dollars per hour. However, even the higher wage rates in states like California and Washington may be lacking - one analysis found that if minimum wage had kept up with productivity, the minimum hourly wage in the U.S. should have been 22.88 dollars per hour in 2021. Additionally, the impact of decreased purchasing power due to inflation will impact different parts of society in different ways with stark contrast in average wages due to both gender and race.

United States PI: sa: Wage & Salary: Private: Service Industries data was reported at 1,972.000 USD bn in Sep 2003. This records an increase from the previous number of 1,955.400 USD bn for Jun 2003. United States PI: sa: Wage & Salary: Private: Service Industries data is updated quarterly, averaging 154.100 USD bn from Mar 1946 (Median) to Sep 2003, with 231 observations. The data reached an all-time high of 1,972.000 USD bn in Sep 2003 and a record low of 13.500 USD bn in Mar 1946. United States PI: sa: Wage & Salary: Private: Service Industries data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A201: NIPA 1999: Personal Income and Disposition.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over: Women (LEU0257856700A) from 2011 to 2023 about second quartile, occupation, benefits, compensation, full-time, jobs, females, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

United States PI: Wage & Salary: Government data was reported at 891.924 USD bn in Oct 2003. This records an increase from the previous number of 890.604 USD bn for Sep 2003. United States PI: Wage & Salary: Government data is updated monthly, averaging 282.476 USD bn from Jan 1959 (Median) to Oct 2003, with 538 observations. The data reached an all-time high of 894.468 USD bn in Jun 2003 and a record low of 45.348 USD bn in Jan 1959. United States PI: Wage & Salary: Government data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A201: NIPA 1999: Personal Income and Disposition.

📂 Dataset Title:

AI Impact on Job Market: Increasing vs Decreasing Jobs (2024–2030)

📝 Dataset Description:

This dataset explores how Artificial Intelligence (AI) is transforming the global job market. With a focus on identifying which jobs are increasing or decreasing due to AI adoption, this dataset provides insights into job trends, automation risks, education requirements, gender diversity, and other workforce-related factors across industries and countries.

The dataset contains 30,000 rows and 13 valuable columns, generated to reflect realistic labor market patterns based on ongoing research and public data insights. It can be used for data analysis, predictive modeling, AI policy planning, job recommendation systems, and economic forecasting.

📊 Columns Description:

Column Name Description

Job Title Name of the job/role (e.g., Data Analyst, Cashier, etc.) Industry Industry sector in which the job is categorized (e.g., IT, Healthcare, Manufacturing) Job Status Indicates whether the job is Increasing or Decreasing due to AI adoption AI Impact Level Estimated level of AI impact on the job: Low, Moderate, or High Median Salary (USD) Median annual salary for the job in USD Required Education Typical minimum education level required for the job Experience Required (Years) Average number of years of experience required Job Openings (2024) Number of current job openings in 2024 Projected Openings (2030) Projected job openings by the year 2030 Remote Work Ratio (%) Estimated percentage of jobs that can be done remotely Automation Risk (%) Probability of the job being automated or replaced by AI Location Country where the job data is based (e.g., USA, India, UK, etc.) Gender Diversity (%) Approximate percentage representation of non-male genders in the job

🔍 Potential Use Cases:

Predict which jobs are most at risk due to automation.

Compare AI impact across industries and countries.

Build dashboards on workforce diversity and trends.

Forecast job market shifts by 2030.

Train ML models to predict job growth or decline.

📚 Source:

This is a synthetic dataset generated using realistic modeling, public job data patterns (U.S. BLS, OECD, McKinsey, WEF reports), and AI simulation to reflect plausible scenarios from 2024 to 2030. Ideal for educational, research, and AI project purposes.

📌 License: MIT

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over: Men (LEU0257856600A) from 2011 to 2011 about second quartile, occupation, benefits, compensation, males, jobs, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

Graph and download economic data for Personal income per capita (A792RC0A052NBEA) from 1929 to 2024 about personal income, per capita, personal, income, GDP, and USA.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Hatfield: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 25(1.73%) households where the householder is under 25 years old, 636(44.14%) households with a householder aged between 25 and 44 years, 466(32.34%) households with a householder aged between 45 and 64 years, and 314(21.79%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the borough of Hatfield, showcasing varying income levels among different age demographics.

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:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 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 $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Hatfield median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Peoria: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 3,776(7.71%) households where the householder is under 25 years old, 17,193(35.12%) households with a householder aged between 25 and 44 years, 15,028(30.70%) households with a householder aged between 45 and 64 years, and 12,953(26.46%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the city of Peoria, showcasing varying income levels among different age demographics.

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:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 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 $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Peoria median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Brazos County: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 18,268(20.66%) households where the householder is under 25 years old, 32,473(36.73%) households with a householder aged between 25 and 44 years, 23,717(26.82%) households with a householder aged between 45 and 64 years, and 13,957(15.79%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the county of Brazos County, showcasing varying income levels among different age demographics.

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:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 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 $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Brazos County median household income by age. You can refer the same here

About this dataset

Context

The dataset presents median household incomes for various household sizes in Indian Wells, CA, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Indian Wells did not include 6, or 7-person households. Across the different household sizes in Indian Wells the mean income is $162,107, and the standard deviation is $92,325. The coefficient of variation (CV) is 56.95%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households. Please note that the U.S. Census Bureau uses $250,001 as a JAM value to report incomes of $250,000 or more. In the case of Indian Wells, there were 1 household sizes where the JAM values were used. Thus, the numbers for the mean and standard deviation may not be entirely accurate and have a higher possibility of errors. However, to obtain an approximate estimate, we have used a value of $250,001 as the income for calculations, as reported in the datasets by the U.S. Census Bureau.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $35,828. It then further increased to $120,743 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/indian-wells-ca-median-household-income-by-household-size.jpeg" alt="Indian Wells, CA median household income, by household size (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.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Indian Wells median household income. You can refer the same here

United States PI: Wage & Salary: Private: Distributive Industries data was reported at 1,136.658 USD bn in Oct 2003. This records an increase from the previous number of 1,134.377 USD bn for Sep 2003. United States PI: Wage & Salary: Private: Distributive Industries data is updated monthly, averaging 366.618 USD bn from Jan 1959 (Median) to Oct 2003, with 538 observations. The data reached an all-time high of 1,136.658 USD bn in Oct 2003 and a record low of 63.347 USD bn in Jan 1959. United States PI: Wage & Salary: Private: Distributive Industries data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A201: NIPA 1999: Personal Income and Disposition.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Bergen County: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 4,517(1.28%) households where the householder is under 25 years old, 102,883(29.12%) households with a householder aged between 25 and 44 years, 146,842(41.56%) households with a householder aged between 45 and 64 years, and 99,065(28.04%) households where the householder is over 65 years old.
• In Bergen County, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

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:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 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 $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Bergen County median household income by age. You can refer the same here