About this dataset

Context

The dataset tabulates the Moe township population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Moe township. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 353 (52.61% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Moe township population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Moe township is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Moe township is shown in the following column.

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 Moe township Population by Age. You can refer the same here

Current clamp measurements collected on various small electronic devices. Details on the data set can be found in J. M. Vann, T. P. Karnowski, R. Kerekes, C. D. Cooke and A. L. Anderson, "A Dimensionally Aligned Signal Projection for Classification of Unintended Radiated Emissions," in IEEE Transactions on Electromagnetic Compatibility, vol. 60, no. 1, pp. 122-131, Feb. 2018, doi: 10.1109/TEMC.2017.2692962.

Comprehensive dataset containing 4 verified Moe locations in United States with complete contact information, ratings, reviews, and location data.

This dataset contains the predicted prices of MOE for the upcoming years based on user-defined projections.

This dataset contains the predicted prices of the asset MOE over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset provides information about the number of properties, residents, and average property values for Moe Moe Place cross streets in Wahiawa, HI.

This dataset provides information about the number of properties, residents, and average property values for Moe Lane cross streets in Topsham, ME.

Towns in Time is a compilation of time series data for Victoria's towns covering the years 1981 to 2011. The data is based on Census data collected by the Australian Bureau of Statistics. Towns in Time presents 2011 data for the 2011 definition of each town, together with data under the 2006 definition for 2006 and earlier years. A map showing the difference in the town's boundaries between 2006 and 2011 is attached to each data sheet. It is recommended the user assess this concordance when using time series data.

Towns in Time is a compilation of time series data for Victoria's towns covering the years 1981 to 2011. The data is based on Census data collected by the Australian Bureau of Statistics. Towns in Time presents 2011 data for the 2011 definition of each town, together with data under the 2006 definition for 2006 and earlier years. A map showing the difference in the town's boundaries between 2006 and 2011 is attached to each data sheet. It is recommended the user assess this concordance when using time series data.

Data from 68 southern pine hybrid trees (Pinus elliottii var. elliottii x P. caribaea var. hondurensis) sampled in southern Queensland (note no data exists for tree 61, hence tree numbers range from 1 to 69). The trees were collected from three sites in the southeast Queensland plantation estate owned by HQPlantations. Tree sizes were stratified by diameter at breast height, to ensure we collected the full range of sizes in the plantations. Ages of the trees ranged from 19 to 28 years.

Two csv data files:

File: Data for A new approach for predicting board MOE from increment cores - board data.csv

6 variables in columns and 635 lines of hybrid pine data: 1. Tree#: Identifier for the tree 2. Stud centre distance from pith (mm): Distance from the pith to the centre of the board 3. Log end: The end of the log from which the static bending sample was taken. Butt end = 0, Top end = 1. 4. Static bending MOE: The standard reference MOE measured using the four-point bending test. 5. Predicted MOE - 3D approach: The board MOE predicted from our three-dimensional approach using four diametrical cores extracted from the tree. 6. The board MOE predicted from our two-dimensional approach using a single diametrical core extracted near breast height.

File: Data for A new approach for predicting board MOE from increment cores - core data.csv

9 variables in columns and 3184 lines of hybrid pine data:

1. Tree#: Identifier for the tree

2. Stocking: Number of stems per hectare

3. Height Core#: The core number extracted from the log, from 1 (butt end) to 4 (top end).

4. Side#: The side of the pith the segment was taken from.

5. Segment Position#: Segment count from each side of the pith, starting from 1 (near bark).

6. Segment#: Overall segment number. Note some segments were rejected hence maximum segment number is 3204.

7. Distance Seg from pith (Matlab): Distance from the pith to the centre of the segment, calculated using image processing in Matlab.

8. Height (m): Height of the core in the tree.

9. Segment US MOE: Segment MOE (in MPa) measured using the ultrasound method.

This dataset provides information about the number of properties, residents, and average property values for Moe Road cross streets in Mondovi, WI.

Medium-accuracy Orbit Ephemeris (MOE) providing position and velocity vectors of satellite center of mass used in forward stream processing. MOE products are organized into daily files, spanning 26 hours and centered at 12:00:00 (TAI) of each day (i.e., from day D-1 23:00 to day D+1 01:00 TAI time). Available in netCDF-4 file format with latency of < 1.5 days.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Based on professional technical analysis and AI models, deliver precise price‑prediction data for MOE on 2025-10-09. Includes multi‑scenario analysis (bullish, baseline, bearish), risk assessment, technical‑indicator insights and market‑trend forecasts to help investors make informed trading decisions and craft sound investment strategies.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most States are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, and municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four States (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their States. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The 2010 Census boundaries for counties and equivalent entities are as of January 1, 2010, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

This table contains data on educational attainment from the American Community Survey 2006-2010 database for counties. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

The name for table 'ACS10EDUCNTYMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

The TANF Financial Data tables compile Federal TANF and State MOE expenditures for reported by states by fiscal year. Units of Response: States Type of Data: Financial Tribal Data: No Periodicity: Annual Demographic Indicators: Not Applicable SORN: Not Applicable Data Use Agreement: https://www.icpsr.umich.edu/rpxlogin Data Use Agreement Location: Unavailable Granularity: State Spatial: United States Geocoding: State

Comprehensive dataset containing 1 verified Moe locations in Argentina with complete contact information, ratings, reviews, and location data.

About this dataset

Context

The dataset tabulates the data for the Moe Township, Minnesota population pyramid, which represents the Moe township population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Moe Township, Minnesota, is 27.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Moe Township, Minnesota, is 55.3.
• Total dependency ratio for Moe Township, Minnesota is 82.8.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Moe Township, Minnesota is 1.8.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Moe township population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Moe township for the selected age group is shown in the following column.
• Population (Female): The female population in the Moe township for the selected age group is shown in the following column.
• Total Population: The total population of the Moe township for the selected age group is shown in the following column.

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 Moe township Population by Age. You can refer the same here

Gravity data measures small changes in gravity due to changes in the density of rocks beneath the Earth's surface. The data collected are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose.
This Moe detailed gravity (P198643) contains a total of 86 point data values acquired at a spacing of 50 metres. The data is located in VIC and were acquired in 1986, under project No. 198643 for Department of Minerals and Energy (Victoria).

This dataset contains the predicted prices of Merchant Moe for the upcoming years based on user-defined projections.