Zip Codes with the Highest Percentage of Population with a Degree in Psychology in Watertown, WI

Q: What are the Top Zip Codes with the Highest Percentage of Population with a Degree in Psychology in Watertown, WI?

Top Zip Codes with the Highest Percentage of Population with a Degree in Psychology in Watertown, WI are: #1 53094 7.2% . #2 53098 2.3% .

Q: What zip code has the Highest Percentage of Population with a Degree in Psychology in Watertown, WI?

53094 has the Highest Percentage of Population with a Degree in Psychology in Watertown, WI with 7.2%.

Q: What is the Percentage of Population with a Degree in Psychology in Wisconsin?

Percentage of Population with a Degree in Psychology in Wisconsin is 4.6%.

Q: What is the Percentage of Population with a Degree in Psychology in the United States?

Percentage of Population with a Degree in Psychology in the United States is 5.1%.

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Psychology

Population

Highest Population Highest Population Density Lowest Population Density Male / Female Ratio Female / Male Ratio Oldest Population Oldest Population | Male Oldest Population | Female Youngest Population Youngest Population | Male Youngest Population | Female

Families and Households

Largest Family Size Largest Household Size Most Single Fathers Most Single Mothers Fewest Single Fathers Fewest Single Mothers Smallest Family Size Smallest Household Size

Female Fertility

Female Fertility (Unmarried)

Highest Illegitimacy | All Women Lowest Illegitimacy | All Women

Race (Community Size)

Asian Black / African American Hispanic or Latino Native / Alaskan White / Caucasian

Race (Percentage)

Asian Black / African American Hispanic or Latino Native / Alaskan White / Caucasian

Ancestry (Community Size)

American Austrian British Central American Croatian Czech Czechoslovakian Danish Dutch English European Finnish French French Canadian German Greek Hungarian Indian (Asian)Irish Italian Mexican Norwegian Polish Puerto Rican Russian Scandinavian Scotch-Irish Scottish Slovak Slovene South American Spaniard Subsaharan African Swedish Swiss Ukrainian Venezuelan Welsh

Ancestry (Percentage)

Immigrant Origin (Total)

Asia Central America Eastern Europe Europe Germany Latin America Mexico Netherlands Northern Europe South Eastern Asia Western Europe

Immigrant Origin (Percentage)

Asia Central America Eastern Europe Europe Germany Latin America Mexico Netherlands Northern Europe South Eastern Asia Western Europe

Income

Highest Per Capita Income Highest Earnings | Male Highest Earnings | Female Highest Wage/Income Gap ($)Highest Wage/Income Gap (%)Highest Inequality / Gini Index Lowest Per Capita Income Lowest Earnings | Male Lowest Earnings | Female Lowest Wage/Income Gap ($)Lowest Wage/Income Gap (%)Lowest Inequality / Gini Index

Income (Families)

Highest Family Income Lowest Family Income Family Income | $0-10k Family Income | $100k+Family Income | $200k+

Income (Households)

Highest Household Income Lowest Household Income Household Income | $0-10k Household Income | $200k+Household Income | $100k+

Poverty

Poverty (Families)

Unemployment

Employment Occupations

Architecture & Engineering Arts, Media & Entertainment Business & Financial Cleaning & Maintenance Community & Social Service Computer & Mathematics Computer, Engineering & Science Construction & Extraction Education Instruction & Library Education, Arts & Media Farming, Fishing & Forestry Firefighting & Prevention Food Preparation & Serving Health Diagnosing & Treating Health Technologists Healthcare Support Installation, Maintenance & Repair Law Enforcement Legal Services & Support Life, Physical & Social Science Management Material Moving Office & Administration Personal Care and Service Production Sales & Related Security & Protection Transportation

Employment Industries

Accommodation & Food Services Administrative & Support Services Agriculture, Fishing & Hunting Arts, Entertainment & Recreation Construction Educational Services Enterprise Management Finance & Insurance Health Care & Social Assistance Information & Technology Manufacturing Mining, Quarrying, & Extraction Professional & Scientific Services Public Administration Real Estate, Rental & Leasing Retail Trade Transportation & Warehousing Utilities Wholesale Trade

Employer Class

Private Company Employees Self-Employed / Incorporated Self-Employed / Not Incorporated Not-for-profit Organizations Local Government Employees State Government Employees Federal Government Employees Unpaid Family Workers

Commute Time

Longest Commute Longest Commute | Male Longest Commute | Female Shortest Commute Shortest Commute | Male Shortest Commute | Female

Commute Means

Drive | Alone Drive | Carpool Taxi / Cab Walk to Work Work from Home

School Enrollment

In Private School Nursery / Preschool Kindergarten Elementary School Middle School High School College University

Education by Degree Field

Computers and Mathematics Bio, Nature & Agricultural Physical and Health SciencesPsychologySocial Sciences Engineering Science and Engineering Business Education Literature and Languages Liberal Arts and History Visual and Performing Arts Communications Arts and Humanities

Occupancy

Highest Owner-Occupied Highest Renter-Occupied Lowest Owner-Occupied Lowest Renter-Occupied

Finances

Highest Median Housing Costs Highest Property Prices Highest Owner Housing Costs Highest Renter Housing Costs Highest Housing Costs / Income Lowest Median Housing Costs Lowest Property Prices Lowest Owner Housing Costs Lowest Renter Housing Costs Lowest Housing Costs / Income

Physical Characteristics

Detached Home Residency Condo/Apartment Residency Utility Gas Heating Bottled Gas / LP Heating Electrical Heating Fuel Oil Heating Fuel-less Heating Households without a Cars Households with 1 or more Cars Households with 2 or more Cars Households with 3 or more Cars

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Map of Zip Codes with the Highest Percentage of Population with a Degree in Psychology in Watertown

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