Total Income to Compare:

$

Income Percentile Results

See Similar Occupations

• All Occupations
• Bartenders
• Chefs and Cooks
• Combined Food Preparation and Serving Workers, Including Fast Food
• Counter Attendant, Cafeteria, Food Concession, and Coffee Shop
• First-Line Supervisors of Food Preparation and Serving Workers
• Food Preparation Workers

Income Percentile Stats

• To be in the top 1% for this age range, your household would need an income of $0 per year. This would include salary, investments, and any business income.
• To be in the top 5% for this age range, your household would need an income of $0 per year. This would include salary, investments, and any business income.

Income of by Highest Education Level

Total Income of $55,000 ranks for education levels:

• Compared to Doctoral degree holders this ranks between the NANth and NANth percentiles.
• Compared to Professional degree beyond a Bachelor's degree holders this ranks between the NANth and NANth percentiles.
• Compared to Master's degree holders this ranks between the NANth and NANth percentiles.
• Compared to Bachelor's degree holders this ranks between the NANth and NANth percentiles.
• Compared to HS Diploma / GED degree holders this ranks between the NANth and NANth percentiles.

Income Percentile Distribution by Education Level

Highest Level of Education for :

• Other (N/A or Less than HS): NAN%
• HS Diploma / GED: NAN%
• Associates Degree and Some College: NAN%
• Bachelors Degree: NAN%
• Masters Degree: NAN%
• Professional Degree beyond a Bachelors: NAN%
• Doctoral Degree (PHd) : NAN%

Most Common Bachelors Degree Majors

Note: The source data only records undergraduate degree majors, even if a person continues to study.

Treemap of Undergraduate Majors

Methodology and Assumptions

This data was sourced from the person-level data recorded by the American Communities Survey. The version of the survey used was the most recent 5 year revision for data recorded from 2017-2022. These results represent 0 . The occupation code that was used to generate these results e was 4060 to read more about the occupation codes that the ACS and Census use. These results were generated in R using raw data from the ACS and precalculated in a batch. This data includes all individual income for the survey respondent, so some of the people may have a wage job as well as other income sources. I did not limit to wage income, because many occupations have high portions of entrepreneurs (CEOs, doctors, tradespeople).

Exclusions and Filters Applied:

• Filtered for people who reported working at least 30 hours a week.
• High School Graduates and GED graduates were original 2 separate categories that I combined.
• Anything below High School Graduates is combined into a separate category. I did not include these on the page for space reason but I can.
The data has data for associate degree holders and some college and these values are mostly in between the high school and bachelors samples. There doesn't seem to be a significant difference between some college and an associates degree.
• All ages are included and not separated. I did some initial testing and there is a difference if the data is split out by age, but I wasn't able to consolidate the data into a way that would make it fast to interact with and avoid being too complicated.
• There may be some confusion around a masters degree vs a professional degree beyond a masters. This was a distinction made in the original raw data that I decided to keep. Because the data is collected by polling people individually, some of the respondents may have mixed up the difference depending on how they phrased their response.
  • Masters Degree : MBA, Masters in Something
  • Professional Degree beyond a Bachelors Degree: Law Degree, Medical School, generally these degrees are credentials for specific careers.
  • Doctoral Degree: PHd