Annual descriptive price statistics for each calendar year 2005 – 2024 for 11 Local Government Districts in Northern Ireland. The statistics include: • Minimum sale price • Lower quartile sale price • Median sale price • Simple Mean sale price • Upper Quartile sale price • Maximum sale price • Number of verified sales Prices are available where at least 30 sales were recorded in the area within the calendar year which could be included in the regression model i.e. the following sales are excluded: • Non Arms-Length sales • sales of properties where the habitable space are less than 30m2 or greater than 1000m2 • sales less than £20,000. Annual median or simple mean prices should not be used to calculate the property price change over time. The quality (where quality refers to the combination of all characteristics of a residential property, both physical and locational) of the properties that are sold may differ from one time period to another. For example, sales in one quarter could be disproportionately skewed towards low-quality properties, therefore producing a biased estimate of average price. The median and simple mean prices are not ‘standardised’ and so the varying mix of properties sold in each quarter could give a false impression of the actual change in prices. In order to calculate the pure property price change over time it is necessary to compare like with like, and this can only be achieved if the ‘characteristics-mix’ of properties traded is standardised. To calculate pure property change over time please use the standardised prices in the NI House Price Index Detailed Statistics file.

The Global Drought Hazard Frequency and Distribution is a 2.5 minute grid based upon the International Research Institute for Climate Prediction's (IRI) Weighted Anomaly of Standardized Precipitation (WASP). Utilizing average monthly precipitation data from 1980 through 2000 at a resolution of 2.5 degrees, WASP assesses the precipitation deficit or surplus over a three month temporal window that is weighted by the magnitude of the seasonal cyclic variation in precipitation. The three months' averages are derived from the precipitation data and the median rainfall for the 21 year period is calculated for each grid cell. Grid cells where the three month running average of precipitation is less than 1 mm per day ae excluded. Drought events are identified when the magnitude of a monthly precipitation deficit is less than or equal to 50 percent of its longterm median value for three or more consecutive months. Grid cells are then divided into 10 classes having an approximately equal number of grid cells. Higher grid cell values denote higher frequencies of drought occurrences. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), Columbia University International Research Institute for Climate Prediction (IRI), and Columbia University Center for International Earth Science Information Network (CIESIN).

Annual descriptive price statistics for each calendar year 2005 – 2024 for 462 electoral wards within 11 Local Government Districts. The statistics include: • Minimum sale price • Lower quartile sale price • Median sale price • Simple Mean sale price • Upper Quartile sale price • Maximum sale price • Number of verified sales Prices are available where at least 30 sales were recorded in the area within the calendar year which could be included in the regression model i.e. the following sales are excluded: • Non Arms-Length sales • sales of properties where the habitable space are less than 30m2 or greater than 1000m2 • sales less than £20,000. Annual median or simple mean prices should not be used to calculate the property price change over time. The quality (where quality refers to the combination of all characteristics of a residential property, both physical and locational) of the properties that are sold may differ from one time period to another. For example, sales in one quarter could be disproportionately skewed towards low-quality properties, therefore producing a biased estimate of average price. The median and simple mean prices are not ‘standardised’ and so the varying mix of properties sold in each quarter could give a false impression of the actual change in prices. In order to calculate the pure property price change over time it is necessary to compare like with like, and this can only be achieved if the ‘characteristics-mix’ of properties traded is standardised. To calculate pure property change over time please use the standardised prices in the NI House Price Index Detailed Statistics file.

• Maximum sale price • Number of verified sales Prices are available where at least 30 sales were recorded in the area within the calendar year which could be included in the regression model i.e. the following sales are excluded: • Non Arms-Length sales • sales of properties where the habitable space are less than 30m2 or greater than 1000m2 • sales less than £20,000. Annual median or simple mean prices should not be used to calculate the property price change over time. The quality (where quality refers to the combination of all characteristics of a residential property, both physical and locational) of the properties that are sold may differ from one time period to another. For example, sales in one quarter could be disproportionately skewed towards low-quality properties, therefore producing a biased estimate of average price. The median and simple mean prices are not ‘standardised’ and so the varying mix of properties sold in each quarter could give a false impression of the actual change in prices. In order to calculate the pure property price change over time it is necessary to compare like with like, and this can only be achieved if the ‘characteristics-mix’ of properties traded is standardised. To calculate pure property change over time please use the standardised prices in the NI House Price Index Detailed Statistics file.

The Global Drought Hazard Frequency and Distribution is a 2.5 minute grid based upon the International Research Institute for Climate Prediction's (IRI) Weighted Anomaly of Standardized Precipitation (WASP). Utilizing average monthly precipitation data from 1980 through 2000 at a resolution of 2.5 degrees, WASP assesses the precipitation deficit or surplus over a three month temporal window that is weighted by the magnitude of the seasonal cyclic variation in precipitation. The three months' averages are derived from the precipitation data and the median rainfall for the 21 year period is calculated for each grid cell. Grid cells where the three month running average of precipitation is less than 1 mm per day ae excluded. Drought events are identified when the magnitude of a monthly precipitation deficit is less than or equal to 50 percent of its longterm median value for three or more consecutive months. Grid cells are then divided into 10 classes having an approximately equal number of grid cells. Higher grid cell values denote higher frequencies of drought occurrences. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), Columbia University International Research Institute for Climate Prediction (IRI), and Columbia University Center for International Earth Science Information Network (CIESIN).

About this dataset

Context

The dataset presents median household incomes for various household sizes in Williams Bay, WI, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, all of the household sizes were found in Williams Bay. Across the different household sizes in Williams Bay the mean income is $124,102, and the standard deviation is $81,319. The coefficient of variation (CV) is 65.53%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households. Please note that the U.S. Census Bureau uses $250,001 as a JAM value to report incomes of $250,000 or more. In the case of Williams Bay, there were 1 household sizes where the JAM values were used. Thus, the numbers for the mean and standard deviation may not be entirely accurate and have a higher possibility of errors. However, to obtain an approximate estimate, we have used a value of $250,001 as the income for calculations, as reported in the datasets by the U.S. Census Bureau.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $26,542. It then further increased to $45,564 for 7-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/williams-bay-wi-median-household-income-by-household-size.jpeg" alt="Williams Bay, WI median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Williams Bay median household income. You can refer the same here