About this application: This application provides summary profiles showing frequently requested data items from various US Census Bureau programs. Profiles are available for the nation, states, and counties.
Per capita income in past 12 months (in 2018 dollars), 2014-2018 - (US Dollars)
County
Value
Alameda
44,283
Alpine
29,041
Amador
30,100
Butte
27,537
Calaveras
32,494
Colusa
27,336
Contra Costa
45,524
Del Norte
22,832
El Dorado
40,382
Fresno
23,284
Glenn
21,736
Humboldt
26,747
Imperial
17,590
Inyo
31,540
Kern
22,553
Kings
21,186
Lake
25,404
Lassen
21,897
Los Angeles
32,469
Madera
21,394
Marin
69,275
Mariposa
29,776
Mendocino
27,395
Merced
21,634
Modoc
23,235
Mono
33,421
Monterey
28,836
Napa
42,677
Nevada
37,145
Orange
39,590
Placer
41,508
Plumas
32,710
Riverside
27,142
Sacramento
31,311
San Benito
31,475
San Bernardino
23,956
San Diego
36,156
San Francisco
64,157
San Joaquin
26,145
San Luis Obispo
35,832
San Mateo
57,375
Santa Barbara
34,229
Santa Clara
52,451
Santa Cruz
39,001
Shasta
27,983
Sierra
31,972
Siskiyou
28,130
Solano
33,700
Sonoma
39,929
Stanislaus
25,101
Sutter
26,070
Tehama
23,126
Trinity
25,964
Tulare
20,421
Tuolumne
33,685
Ventura
36,891
Yolo
32,598
Yuba
23,867
Value for California (US Dollars): $35,021
Sources: U.S. Census Bureau, American Community Survey (ACS) and Puerto Rico Community Survey (PRCS), 5-Year Estimates. The PRCS is part of the Census Bureau's ACS, customized for Puerto Rico. Both Surveys are updated every year.
Definition
Per capita income is the mean income computed for every man, woman, and child in a particular group including those living in group quarters. It is derived by dividing the aggregate income of a particular group by the total population in that group. This measure is rounded to the nearest whole dollar. For the complete definition, go to ACS subject definitions "Income in the Past 12 Months, Per Capita Income."
Source and Accuracy
This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12 month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.
Statistics from all surveys are subject to sampling and nonsampling error. Sampling error is the uncertainty between an estimate based on a sample and the corresponding value that would be obtained if the estimate were based on the entire population (as from a census). Measures of sampling error are provided in the form of margins of error for all estimates included with ACS and PRCS published products. The Census Bureau recommends that data users incorporate this information into their analyses, as sampling error in survey estimates could impact the conclusions drawn from the results. The data for each geographic area are presented together with margins of error at Using margins of error. A more detailed explanation of margins of error and a demonstration of how to use them is provided below.
For more information on sampling and estimation methodology, confidentiality, and sampling and nonsampling errors, please see the Multiyear Accuracy (US) and the Multiyear Accuracy (Puerto Rico) documents at "Documentation - Accuracy of the data."
Margin of Error
As mentioned above, ACS estimates are based on a sample and are subject to sampling error. The margin of error measures the degree of uncertainty caused by sampling error. The margin of error is used with an ACS estimate to construct a confidence interval about the estimate. The interval is formed by adding the margin of error to the estimate (the upper bound) and subtracting the margin of error from the estimate (the lower bound). It is expected with 90 percent confidence that the interval will contain the full population value of the estimate. The following example is for demonstrating purposes only. Suppose the ACS reported that the percentage of people in a state who were 25 years and older with a bachelor's degree was 21.3 percent and that the margin of error associated with this estimate was 0.7 percent. By adding and subtracting the margin of error from the estimate, we calculate the 90-percent confidence interval for this estimate:
Therefore, we can be 90 percent confident that the percent of the population 25 years and older having a bachelor's degree in a state falls somewhere between 20.6 percent and 22.0 percent.