NOTE: THIS DATA FILE WILL CHANGE! To improve accessibility of data for all users, we will convert this file from a text format to an html table by the end of June 2024. Title: 90% Confidence Interval Upper Bound of Estimate of Median Household Income for Lyman County, SD Series ID: MHICIUBSD46085A052NCEN 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 2022-01-01 Last Updated: 2023-12-14 1:51 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 (https://www.census.gov/programs-surveys/saipe/about.html) (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 (https://www.census.gov/programs-surveys/saipe/guidance/confidence-intervals.html). DATE VALUE 1989-01-01 23491 1990-01-01 . 1991-01-01 . 1992-01-01 . 1993-01-01 28901 1994-01-01 . 1995-01-01 29985 1996-01-01 . 1997-01-01 30486 1998-01-01 30847 1999-01-01 30068 2000-01-01 32331 2001-01-01 31682 2002-01-01 29391 2003-01-01 31630 2004-01-01 32058 2005-01-01 33595 2006-01-01 33463 2007-01-01 35156 2008-01-01 39696 2009-01-01 37686 2010-01-01 42967 2011-01-01 41796 2012-01-01 44593 2013-01-01 43865 2014-01-01 44779 2015-01-01 43258 2016-01-01 46945 2017-01-01 48103 2018-01-01 51609 2019-01-01 51057 2020-01-01 49496 2021-01-01 53790 2022-01-01 60974