Federal Reserve Economic Data

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

Title 90% Confidence Interval Upper Bound of Estimate of Median Household Income for Sanborn County, SD
Series ID MHICIUBSD46111A052NCEN
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 2023-01-01
Last Updated 2024-12-20 3:11 AM 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 19219
1990-01-01 .
1991-01-01 .
1992-01-01 .
1993-01-01 27396
1994-01-01 .
1995-01-01 28268
1996-01-01 .
1997-01-01 32032
1998-01-01 32730
1999-01-01 34885
2000-01-01 37310
2001-01-01 36970
2002-01-01 35565
2003-01-01 37895
2004-01-01 37973
2005-01-01 38313
2006-01-01 41256
2007-01-01 44699
2008-01-01 47316
2009-01-01 44906
2010-01-01 47558
2011-01-01 51529
2012-01-01 49123
2013-01-01 50975
2014-01-01 51039
2015-01-01 54029
2016-01-01 56344
2017-01-01 53659
2018-01-01 58238
2019-01-01 62807
2020-01-01 59682
2021-01-01 68081
2022-01-01 70597
2023-01-01 74865

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