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The dataset presents median household incomes for various household sizes in Indian Head, MD, 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
https://i.neilsberg.com/ch/indian-head-md-median-household-income-by-household-size.jpeg" alt="Indian Head, MD median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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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.
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/.
This dataset is a part of the main dataset for Indian Head median household income. You can refer the same here
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TwitterThe statistic shows the average number of residents living in India's households in 2012, by state and union territory. In that year, Punjab and Arunachal Pradesh had an average of **** people living in a household, while the lowest average size was in Tamil Nadu with *** people per household.
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The dataset tabulates the median household income in Indian Village. It can be utilized to understand the trend in median household income and to analyze the income distribution in Indian Village by household type, size, and across various income brackets.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Indian Village median household income. You can refer the same here
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TwitterAccording to a survey conducted in 2015 across India, over ** percent of the surveyed households had an average monthly income up to 10,000 Indian rupees. This percentage varied among the rural and urban areas, where over ** percent of the rural households and ** percent of the urban households earned up to 10,000 Indian rupees monthly. India had a high rate of rural to urban migration, as Indian cities provided better standards of living and employment opportunities.
Multiple income generators
For most of the population, income is earned in form of wages or salary, rent from residential or commercial property, interest from financial investments, and profits from family businesses. Most Indian households have multiple earning members to support consumption expenses on a day to day basis. During the surveyed year, around ** percent of the households had a single earner, mostly the head of the family, followed by about ** percent of households with two earning members.
Employment scenario
There are a lot of uncertainties in the job market in India. Non-availability of jobs matching education and skills was one of the main reasons for unemployment among Indian graduates. Underemployment was also a problem, and it was higher in urban areas than rural ones. Even though a majority of the population was self-employed, most jobs taken by workers had no written job contracts in both the salaried and casual employment sectors.
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TwitterIn 2019, the average household size of Hindus in Asia-Pacific was *** people per household. In comparison, Hindus in sub-Saharan Africa had the smallest average household size, at *** people per household. The majority of Hindus live in India.
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Graph and download economic data for Estimate of Median Household Income for Indian River County, FL (MHIFL12061A052NCEN) from 1989 to 2023 about Indian River County, FL; Sebastian; FL; households; median; income; and USA.
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** Apologies in advance for sharing the data in XLSX format but had no other choice as I wanted to present/share all the crucial information in 1 single file. **
Several studies in the past have shown that the average height of adults across the globe is is on the rise, but against this trend, the average height of adults in India is declining at an alarming rate, as per a study titled ‘Trends of adult height in India from 1998 to 2015: Evidence from the National Family and Health Survey’.
The authors of this study have stated, “In the context of an overall increase in average heights worldwide, the decline in the average height of adults in India is alarming and demands an urgent enquiry. The argument for different standards of height for the Indian population as different genetic groups needs further scrutiny.”
The study further states that the decline in the average height of Indian adults is not just because of a genetic factor, but various non-genetic factors have also come into play, such as lifestyle, nutrition, social and economic determinants and so on.
| Table# | Desc | Tab |
|---|---|---|
| 1 | Distribution of mean height of Indian according to the age group | tbl1 |
| 2 | Distribution of mean height of men and women according the age group and religion, years 2005–2006 and 2015–2016. | tbl2 |
| 3 | Distribution of mean height of women according to religion, years 1998–1999 and 2005–2006. | tbl3 |
| 4 | Distribution of mean height of women according to the type of caste or tribe, years 1998–1999 and 2005–2006. | tbl4 |
| 5 | Distribution of mean height of men and women according to the type of caste or tribe, round 2005–2006 and 2015–2016. | tbl5 |
| 6 | Distribution of mean height of men and women according to the residence, 2015–2016 and 2005–2006. | tbl6 |
| 7 | Distribution of mean height of women according to the residence, 1998–1999 and 2005–2006. | tbl7 |
| 8 | Distribution of mean height of men and women according to the wealth index, 2015–2016 and 2005–2006. | tbl8 |
| 9 | State wise distribution of mean height of women according to age group, 2005–2006 and 1998–1999 | tbl9 |
| 10 | State wise distribution of mean height of women according to age group, 2015–2016 and 2005–2006. | tbl10 |
| 11 | State wise distribution of mean height of men according to age group, 2015–2016 and 2005–2006. | tbl11 |
| 12 | Average Human Height By Country | tbl12 |
Citation: Choudhary KK, Das S, Ghodajkar P (2021) Trends of adult height in India from 1998 to 2015: Evidence from the National Family and Health Survey. PLoS ONE 16(9): e0255676. https://doi.org/10.1371/journal.pone.0255676
Average human height by country - wikipedia
Read an article online about the decline of average height of adults in India and got curious about the data the researcher collected over 17 years.
Online Article link here
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TwitterFactor analysis of items in the Indian Family Violence and Control Scale (n = 630) with median percent response and standardizing factor loadings of each item.
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TwitterIn 2022, government or private services accounted for the highest source of income at *** thousand Indian rupees in rural households, while livestock rearing was valued at over **** thousand Indian rupees.
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The dataset presents the median household income across different racial categories in Indian Point. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Indian Point population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 96.16% of the total residents in Indian Point. Notably, the median household income for White households is $62,828. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $62,828.
https://i.neilsberg.com/ch/indian-point-mo-median-household-income-by-race.jpeg" alt="Indian Point median household income diversity across racial categories">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Point median household income by race. You can refer the same here
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India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).
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TwitterIn the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.
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TwitterThe second National Family Health Survey (NFHS-2), conducted in 1998-99, provides information on fertility, mortality, family planning, and important aspects of nutrition, health, and health care. The International Institute for Population Sciences (IIPS) coordinated the survey, which collected information from a nationally representative sample of more than 90,000 ever-married women age 15-49. The NFHS-2 sample covers 99 percent of India's population living in all 26 states. This report is based on the survey data for 25 of the 26 states, however, since data collection in Tripura was delayed due to local problems in the state.
IIPS also coordinated the first National Family Health Survey (NFHS-1) in 1992-93. Most of the types of information collected in NFHS-2 were also collected in the earlier survey, making it possible to identify trends over the intervening period of six and one-half years. In addition, the NFHS-2 questionnaire covered a number of new or expanded topics with important policy implications, such as reproductive health, women's autonomy, domestic violence, women's nutrition, anaemia, and salt iodization.
The NFHS-2 survey was carried out in two phases. Ten states were surveyed in the first phase which began in November 1998 and the remaining states (except Tripura) were surveyed in the second phase which began in March 1999. The field staff collected information from 91,196 households in these 25 states and interviewed 89,199 eligible women in these households. In addition, the survey collected information on 32,393 children born in the three years preceding the survey. One health investigator on each survey team measured the height and weight of eligible women and children and took blood samples to assess the prevalence of anaemia.
SUMMARY OF FINDINGS
POPULATION CHARACTERISTICS
Three-quarters (73 percent) of the population lives in rural areas. The age distribution is typical of populations that have recently experienced a fertility decline, with relatively low proportions in the younger and older age groups. Thirty-six percent of the population is below age 15, and 5 percent is age 65 and above. The sex ratio is 957 females for every 1,000 males in rural areas but only 928 females for every 1,000 males in urban areas, suggesting that more men than women have migrated to urban areas.
The survey provides a variety of demographic and socioeconomic background information. In the country as a whole, 82 percent of household heads are Hindu, 12 percent are Muslim, 3 percent are Christian, and 2 percent are Sikh. Muslims live disproportionately in urban areas, where they comprise 15 percent of household heads. Nineteen percent of household heads belong to scheduled castes, 9 percent belong to scheduled tribes, and 32 percent belong to other backward classes (OBCs). Two-fifths of household heads do not belong to any of these groups.
Questions about housing conditions and the standard of living of households indicate some improvements since the time of NFHS-1. Sixty percent of households in India now have electricity and 39 percent have piped drinking water compared with 51 percent and 33 percent, respectively, at the time of NFHS-1. Sixty-four percent of households have no toilet facility compared with 70 percent at the time of NFHS-1.
About three-fourths (75 percent) of males and half (51 percent) of females age six and above are literate, an increase of 6-8 percentage points from literacy rates at the time of NFHS-1. The percentage of illiterate males varies from 6-7 percent in Mizoram and Kerala to 37 percent in Bihar and the percentage of illiterate females varies from 11 percent in Mizoram and 15 percent in Kerala to 65 percent in Bihar. Seventy-nine percent of children age 6-14 are attending school, up from 68 percent in NFHS-1. The proportion of children attending school has increased for all ages, particularly for girls, but girls continue to lag behind boys in school attendance. Moreover, the disparity in school attendance by sex grows with increasing age of children. At age 6-10, 85 percent of boys attend school compared with 78 percent of girls. By age 15-17, 58 percent of boys attend school compared with 40 percent of girls. The percentage of girls 6-17 attending school varies from 51 percent in Bihar and 56 percent in Rajasthan to over 90 percent in Himachal Pradesh and Kerala.
Women in India tend to marry at an early age. Thirty-four percent of women age 15-19 are already married including 4 percent who are married but gauna has yet to be performed. These proportions are even higher in the rural areas. Older women are more likely than younger women to have married at an early age: 39 percent of women currently age 45-49 married before age 15 compared with 14 percent of women currently age 15-19. Although this indicates that the proportion of women who marry young is declining rapidly, half the women even in the age group 20-24 have married before reaching the legal minimum age of 18 years. On average, women are five years younger than the men they marry. The median age at marriage varies from about 15 years in Madhya Pradesh, Bihar, Uttar Pradesh, Rajasthan, and Andhra Pradesh to 23 years in Goa.
As part of an increasing emphasis on gender issues, NFHS-2 asked women about their participation in household decisionmaking. In India, 91 percent of women are involved in decision-making on at least one of four selected topics. A much lower proportion (52 percent), however, are involved in making decisions about their own health care. There are large variations among states in India with regard to women's involvement in household decisionmaking. More than three out of four women are involved in decisions about their own health care in Himachal Pradesh, Meghalaya, and Punjab compared with about two out of five or less in Madhya Pradesh, Orissa, and Rajasthan. Thirty-nine percent of women do work other than housework, and more than two-thirds of these women work for cash. Only 41 percent of women who earn cash can decide independently how to spend the money that they earn. Forty-three percent of working women report that their earnings constitute at least half of total family earnings, including 18 percent who report that the family is entirely dependent on their earnings. Women's work-participation rates vary from 9 percent in Punjab and 13 percent in Haryana to 60-70 percent in Manipur, Nagaland, and Arunachal Pradesh.
FERTILITY AND FAMILY PLANNING
Fertility continues to decline in India. At current fertility levels, women will have an average of 2.9 children each throughout their childbearing years. The total fertility rate (TFR) is down from 3.4 children per woman at the time of NFHS-1, but is still well above the replacement level of just over two children per woman. There are large variations in fertility among the states in India. Goa and Kerala have attained below replacement level fertility and Karnataka, Himachal Pradesh, Tamil Nadu, and Punjab are at or close to replacement level fertility. By contrast, fertility is 3.3 or more children per woman in Meghalaya, Uttar Pradesh, Rajasthan, Nagaland, Bihar, and Madhya Pradesh. More than one-third to less than half of all births in these latter states are fourth or higher-order births compared with 7-9 percent of births in Kerala, Goa, and Tamil Nadu.
Efforts to encourage the trend towards lower fertility might usefully focus on groups within the population that have higher fertility than average. In India, rural women and women from scheduled tribes and scheduled castes have somewhat higher fertility than other women, but fertility is particularly high for illiterate women, poor women, and Muslim women. Another striking feature is the high level of childbearing among young women. More than half of women age 20-49 had their first birth before reaching age 20, and women age 15-19 account for almost one-fifth of total fertility. Studies in India and elsewhere have shown that health and mortality risks increase when women give birth at such young ages?both for the women themselves and for their children. Family planning programmes focusing on women in this age group could make a significant impact on maternal and child health and help to reduce fertility.
INFANT AND CHILD MORTALITY
NFHS-2 provides estimates of infant and child mortality and examines factors associated with the survival of young children. During the five years preceding the survey, the infant mortality rate was 68 deaths at age 0-11 months per 1,000 live births, substantially lower than 79 per 1,000 in the five years preceding the NFHS-1 survey. The child mortality rate, 29 deaths at age 1-4 years per 1,000 children reaching age one, also declined from the corresponding rate of 33 per 1,000 in NFHS-1. Ninety-five children out of 1,000 born do not live to age five years. Expressed differently, 1 in 15 children die in the first year of life, and 1 in 11 die before reaching age five. Child-survival programmes might usefully focus on specific groups of children with particularly high infant and child mortality rates, such as children who live in rural areas, children whose mothers are illiterate, children belonging to scheduled castes or scheduled tribes, and children from poor households. Infant mortality rates are more than two and one-half times as high for women who did not receive any of the recommended types of maternity related medical care than for mothers who did receive all recommended types of care.
HEALTH, HEALTH CARE, AND NUTRITION
Promotion of maternal and child health has been one of the most important components of the Family Welfare Programme of the Government of India. One goal is for each pregnant woman to receive at least three antenatal check-ups plus two tetanus toxoid injections and a full course of iron and folic acid supplementation. In India, mothers of 65 percent of the children
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The dataset presents median household incomes for various household sizes in Indian Lake, TX, 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
https://i.neilsberg.com/ch/indian-lake-tx-median-household-income-by-household-size.jpeg" alt="Indian Lake, TX median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Lake median household income. You can refer the same here
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HCE: Monthly per Capita Consumer Expenditure: Average: India: Urban data was reported at 2,399.240 INR in 2012. This records an increase from the previous number of 1,785.810 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: India: Urban data is updated yearly, averaging 755.200 INR from Jun 1978 (Median) to 2012, with 6 observations. The data reached an all-time high of 2,399.240 INR in 2012 and a record low of 96.150 INR in 1978. HCE: Monthly per Capita Consumer Expenditure: Average: India: Urban data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB017: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Urban (Discontinued).
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Estimate of Median Household Income for Indian River County, FL was 73686.00000 $ in January of 2023, according to the United States Federal Reserve. Historically, Estimate of Median Household Income for Indian River County, FL reached a record high of 73686.00000 in January of 2023 and a record low of 26974.00000 in January of 1989. Trading Economics provides the current actual value, an historical data chart and related indicators for Estimate of Median Household Income for Indian River County, FL - last updated from the United States Federal Reserve on November of 2025.
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HCE: Monthly per Capita Consumer Expenditure: Average: India: Rural data was reported at 1,278.940 INR in 2012. This records an increase from the previous number of 927.700 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: India: Rural data is updated yearly, averaging 281.400 INR from Jun 1978 (Median) to 2012, with 6 observations. The data reached an all-time high of 1,278.940 INR in 2012 and a record low of 68.890 INR in 1978. HCE: Monthly per Capita Consumer Expenditure: Average: India: Rural data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Rural (Discontinued).
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India: Household consumption as percent of GDP: The latest value from 2024 is 61.49 percent, an increase from 60.19 percent in 2023. In comparison, the world average is 66.87 percent, based on data from 102 countries. Historically, the average for India from 1960 to 2024 is 68.99 percent. The minimum value, 54.72 percent, was reached in 2010 while the maximum of 87.38 percent was recorded in 1960.
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India: Furniture and household maintenance prices, world average = 100: The latest value from 2021 is 47.41 index points, a decline from 50.6 index points in 2017. In comparison, the world average is 82.49 index points, based on data from 165 countries. Historically, the average for India from 2017 to 2021 is 49.01 index points. The minimum value, 47.41 index points, was reached in 2021 while the maximum of 50.6 index points was recorded in 2017.
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HCE: Monthly per Capita Consumer Expenditure: Average: Bihar: Rural data was reported at 1,004.980 INR in 2012. This records an increase from the previous number of 681.030 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: Bihar: Rural data is updated yearly, averaging 417.110 INR from Jun 1994 (Median) to 2012, with 4 observations. The data reached an all-time high of 1,004.980 INR in 2012 and a record low of 218.300 INR in 1994. HCE: Monthly per Capita Consumer Expenditure: Average: Bihar: Rural data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Bihar: Rural (Discontinued).
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Context
The dataset presents median household incomes for various household sizes in Indian Head, MD, 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
https://i.neilsberg.com/ch/indian-head-md-median-household-income-by-household-size.jpeg" alt="Indian Head, MD median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Head median household income. You can refer the same here