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

Beaverhead

28,941

Big Horn

18,560

Blaine

18,155

Broadwater

32,362

Carbon

32,553

Carter

32,001

Cascade

29,212

Chouteau

22,661

Custer

30,123

Daniels

34,799

Dawson

32,501

Deer Lodge

25,742

Fallon

34,329

Fergus

29,237

Flathead

30,068

Gallatin

34,331

Garfield

27,291

Glacier

17,219

Golden Valley

27,476

Granite

29,074

Hill

23,017

Jefferson

32,133

Judith Basin

29,827

Lake

24,912

Lewis and Clark

32,433

Liberty

45,587

Lincoln

24,082

Madison

34,014

McCone

27,365

Meagher

23,972

Mineral

23,744

Missoula

30,636

Musselshell

22,737

Park

32,133

Petroleum

32,565

Phillips

23,533

Pondera

24,392

Powder River

30,969

Powell

25,060

Prairie

28,087

Ravalli

27,766

Richland

31,849

Roosevelt

18,813

Rosebud

23,471

Sanders

23,822

Sheridan

33,711

Silver Bow

26,224

Stillwater

32,061

Sweet Grass

29,649

Teton

27,402

Toole

26,434

Treasure

26,348

Valley

28,899

Wheatland

21,442

Wibaux

23,137

Yellowstone

33,007

Value for Montana (US Dollars): $29,765

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.