Table Data - 90% Confidence Interval Upper Bound of Estimate of Median Household Income for Lincoln County, SD

Title 90% Confidence Interval Upper Bound of Estimate of Median Household Income for Lincoln County, SD
Series ID MHICIUBSD46083A052NCEN
Source U.S. Census Bureau
Release Small Area Income and Poverty Estimates
Seasonal Adjustment Not Seasonally Adjusted
Frequency Annual
Units Dollars
Date Range 1989-01-01 to 2024-01-01
Last Updated 2026-02-09 7:03 PM CST
Notes The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs.

Household income includes income of the householder and all other people 15 years and older in the household, whether or not they are related to the householder. Median is the point that divides the household income distributions into two halves: one-half with income above the median and the other with income below the median. The median is based on the income distribution of all households, including those with no income.

A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. A confidence interval is also itself an estimate. It is made using a model of how sampling, interviewing, measuring, and modeling contribute to uncertainty about the relation between the true value of the quantity we are estimating and our estimate of that value. The "90%" in the confidence interval listed above represents a level of certainty about our estimate. If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. For more details about the confidence intervals and their interpretation, see this explanation.
DATE VALUE
1989-01-01 30468
1990-01-01 .
1991-01-01 .
1992-01-01 .
1993-01-01 38291
1994-01-01 .
1995-01-01 43024
1996-01-01 .
1997-01-01 48970
1998-01-01 51594
1999-01-01 53284
2000-01-01 55840
2001-01-01 57109
2002-01-01 60162
2003-01-01 63914
2004-01-01 63728
2005-01-01 64400
2006-01-01 68643
2007-01-01 68109
2008-01-01 75192
2009-01-01 78352
2010-01-01 78989
2011-01-01 82382
2012-01-01 85064
2013-01-01 83661
2014-01-01 85562
2015-01-01 80507
2016-01-01 91446
2017-01-01 95932
2018-01-01 93293
2019-01-01 93640
2020-01-01 91833
2021-01-01 99678
2022-01-01 107097
2023-01-01 109654
2024-01-01 115197

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