Among the states in India, Kerala had the highest literary rate with ** percent in 2011. Chandigarh, Himachal Pradesh and the capital territory of Delhi followed Kerala with above average literacy rates. Notably, all the leading states in the country had more literate males than females at the time of the census.

The data shows the year-wise and state or union territory-wise literacy and rural and urban literacy, for male, female, and total literacy, in India according to Census.

Note: 1. Literacy rate is defined as the population of literates in the population aged 7 year and above. 2. The 1991 data (Excluding Jammu & Kashmir)and 2001 data (Excludes figures of Paomata, Mao Maran and Pura sub-divisions of Senapati district of Manipur for 2001) refer to Census of India.

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

Analysis of ‘Govt Of India Literacy Rate’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/doncorleone92/govt-of-india-literacy-rate on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Context

This is the official dataset released by the govt. of India based on the census 2001 and 2011 survey.

Content

The data is of 35 Indian states and union territories. The literacy rate is spread across the major parameters - Overall, Rural and Urban. All the data is percentage of the total population of that state.

Acknowledgements

Derived from the govt. of India's official site.

Inspiration

Understand the literacy rate in India and which states/UT's have the highest growth in terms of increased literacy rates.

--- Original source retains full ownership of the source dataset ---

The statistic displays the main states and union territories in India with the highest number of illiterate people in 2011. In that year, Uttar Pradesh was at the top of the list, with more than ** million illiterate people, followed by the state of Bihar with over ** million people.

Documentation

Description and codebook for subset of harmonized variables:

Section 2

Guide to datasets:

Full Project Name: The Impact of Mother Literacy and Participation Programs on Child Learning in India

Unique ID: 458

PIs: Rukmini Banerji, James Berry, Marc Shotland

Location: Indian states of Bihar and Rajasthan

Sample: Around 9,000 households in 480 villages

Timeline: 2010 to 2012

Target Group: Children Parents Rural population Women and girls

Outcome of Interest: Employment, Student learning ,Women’s/girls’ decision-making, Gender attitudes and norms

Intervention Type: Early childhood development, Tracking and remedial education, Empowerment training

Associated publications: https://www.aeaweb.org/articles?id=10.1257/app.20150390

More information: https://www.povertyactionlab.org/evaluation/impact-mother-literacy-and-participation-programs-child-learning-india

Dataverse: Banerji, Rukmini; Berry, James; Shotland, Marc, 2017, “The Impact of Maternal Literacy and Participation Programs: Evidence from a Randomized Evaluation in India”, https://doi.org/10.7910/DVN/19PPE7, Harvard Dataverse, V1

Section 3

Survey instrument:

Testing tools:

Section 4

Survey instrument:

Testing tools:

Section 5

No associated survey instrument

Section 6

This dataset was created on 2021-10-06 20:35:41.921 by merging multiple datasets together. The source datasets for this version were:

Maternal Literacy in India Baseline: Modified from ml_merged : contains data with variables only from baseline surveys

Maternal Literacy in India Endline: Modified from ml_merged : contains data with variables only from endline surveys

Maternal Literacy in India Raw Administrative Statistics: ml_admin_stats_raw: Contains administrative statistics from the 2011 census and aser surveys used in online Appendix Table 1 in the paper; this is merged with some of the survey data to create ml_admin_stats

Literacy Rate: Tamil Nadu data was reported at 80.100 % in 12-01-2011. This records an increase from the previous number of 73.450 % for 12-01-2001. Literacy Rate: Tamil Nadu data is updated decadal, averaging 58.525 % from Dec 1961 (Median) to 12-01-2011, with 6 observations. The data reached an all-time high of 80.100 % in 12-01-2011 and a record low of 36.390 % in 12-01-1961. Literacy Rate: Tamil Nadu data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Education Sector – Table IN.EDA001: Literacy Rate.

Analysis of ‘Education in India’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/rajanand/education-in-india on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Would you like to learn SQL to analyze datasets like this? Get your FREE pdf copy of daily SQL learning plan.

Context

When India got independence from British in 1947 the literacy rate was 12.2% and as per the recent census 2011 it is 74.0%. Although it looks an accomplishment, still many people are there without access to education.

It would be interesting to know the current status of the Indian education system.

Content

This dataset contains district and state wise Indian primary and secondary school education data for 2015-16.

Granularity: Annual

List of files:

1. 2015_16_Districtwise.csv ( 680 observations and 819 variables )
2. 2015_16_Statewise_Elementary.csv ( 36 observations and 816 variables )
3. 2015_16_Statewise_Secondary.csv ( 36 observations and 630 variables )

Acknowledgements

Ministry of Human Resource Development (DISE) has shared the dataset here and also published some reports.

Source of Banner image.

Inspiration

This dataset provides the complete information about primary and secondary education. There are many inferences can be made from this dataset. There are few things I would like to understand from this dataset.

1. Drop out ratio in primary and secondary education. (Govt. has made law that every child under age 14 should get free compulsary education.)
2. Various factors affecting examination results of the students.
3. What are all the factors that makes the difference (in literacy rate) between Kerala and Bihar?
4. What could be done to improve the female literacy rate and literacy rate in rural area?

Become a SQL developer in 8 weeks.

Would you like to learn SQL to analyze datasets like this? Get your FREE pdf copy of daily SQL learning plan.

If you have any question, you may contact me via an email or LinkedIn message.

--- Original source retains full ownership of the source dataset ---

Literacy Rate: Kerala data was reported at 94.000 % in 12-01-2011. This records an increase from the previous number of 90.860 % for 12-01-2001. Literacy Rate: Kerala data is updated decadal, averaging 78.850 % from Dec 1951 (Median) to 12-01-2011, with 7 observations. The data reached an all-time high of 94.000 % in 12-01-2011 and a record low of 47.180 % in 12-01-1951. Literacy Rate: Kerala data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Education Sector – Table IN.EDA001: Literacy Rate.

Abstract

The National Family Health Surveys (NFHS) programme, initiated in the early 1990s, has emerged as a nationally important source of data on population, health, and nutrition for India and its states. The 2005-06 National Family Health Survey (NFHS-3), the third in the series of these national surveys, was preceded by NFHS-1 in 1992-93 and NFHS-2 in 1998-99. Like NFHS-1 and NFHS-2, NFHS-3 was designed to provide estimates of important indicators on family welfare, maternal and child health, and nutrition. In addition, NFHS-3 provides information on several new and emerging issues, including family life education, safe injections, perinatal mortality, adolescent reproductive health, high-risk sexual behaviour, tuberculosis, and malaria. Further, unlike the earlier surveys in which only ever-married women age 15-49 were eligible for individual interviews, NFHS-3 interviewed all women age 15-49 and all men age 15-54. Information on nutritional status, including the prevalence of anaemia, is provided in NFHS3 for women age 15-49, men age 15-54, and young children.

A special feature of NFHS-3 is the inclusion of testing of the adult population for HIV. NFHS-3 is the first nationwide community-based survey in India to provide an estimate of HIV prevalence in the general population. Specifically, NFHS-3 provides estimates of HIV prevalence among women age 15-49 and men age 15-54 for all of India, and separately for Uttar Pradesh and for Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu, five out of the six states classified by the National AIDS Control Organization (NACO) as high HIV prevalence states. No estimate of HIV prevalence is being provided for Nagaland, the sixth high HIV prevalence state, due to strong local opposition to the collection of blood samples.

NFHS-3 covered all 29 states in India, which comprise more than 99 percent of India's population. NFHS-3 is designed to provide estimates of key indicators for India as a whole and, with the exception of HIV prevalence, for all 29 states by urban-rural residence. Additionally, NFHS-3 provides estimates for the slum and non-slum populations of eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur. NFHS-3 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOHFW), Government of India, and is the result of the collaborative efforts of a large number of organizations. The International Institute for Population Sciences (IIPS), Mumbai, was designated by MOHFW as the nodal agency for the project. Funding for NFHS-3 was provided by the United States Agency for International Development (USAID), DFID, the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and MOHFW. Macro International, USA, provided technical assistance at all stages of the NFHS-3 project. NACO and the National AIDS Research Institute (NARI) provided technical assistance for the HIV component of NFHS-3. Eighteen Research Organizations, including six Population Research Centres, shouldered the responsibility of conducting the survey in the different states of India and producing electronic data files.

The survey used a uniform sample design, questionnaires (translated into 18 Indian languages), field procedures, and procedures for biomarker measurements throughout the country to facilitate comparability across the states and to ensure the highest possible data quality. The contents of the questionnaires were decided through an extensive collaborative process in early 2005. Based on provisional data, two national-level fact sheets and 29 state fact sheets that provide estimates of more than 50 key indicators of population, health, family welfare, and nutrition have already been released. The basic objective of releasing fact sheets within a very short period after the completion of data collection was to provide immediate feedback to planners and programme managers on key process indicators.

Geographic coverage

• National (29 states )
• Regional (for HIV Prevalence : Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu)
• Local (population and health indicators for slum and non-slum populations for eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur)

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Universe

The population covered by the 2005 DHS is defined as the universe of all ever-married women age 15-49, NFHS-3 included never married women age 15-49 and both ever-married and never married men age 15-54 as eligible respondents.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE

Since a large number of the key indicators to be estimated from NFHS-3 refer to ever-married women in the reproductive ages of 15-49, the target sample size for each state in NFHS-3 was estimated in terms of the number of ever-married women in the reproductive ages to be interviewed.

The initial target sample size was 4,000 completed interviews with ever-married women in states with a 2001 population of more than 30 million, 3,000 completed interviews with ever-married women in states with a 2001 population between 5 and 30 million, and 1,500 completed interviews with ever-married women in states with a population of less than 5 million. In addition, because of sample-size adjustments required to meet the need for HIV prevalence estimates for the high HIV prevalence states and Uttar Pradesh and for slum and non-slum estimates in eight selected cities, the sample size in some states was higher than that fixed by the above criteria. The target sample was increased for Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland, Tamil Nadu, and Uttar Pradesh to permit the calculation of reliable HIV prevalence estimates for each of these states. The sample size in Andhra Pradesh, Delhi, Maharashtra, Tamil Nadu, Madhya Pradesh, and West Bengal was increased to allow separate estimates for slum and non-slum populations in the cities of Chennai, Delhi, Hyderabad, Indore, Kolkata, Mumbai, Meerut, and Nagpur.

The target sample size for HIV tests was estimated on the basis of the assumed HIV prevalence rate, the design effect of the sample, and the acceptable level of precision. With an assumed level of HIV prevalence of 1.25 percent and a 15 percent relative standard error, the estimated sample size was 6,400 HIV tests each for men and women in each of the high HIV prevalence states. At the national level, the assumed level of HIV prevalence of less than 1 percent (0.92 percent) and less than a 5 percent relative standard error yielded a target of 125,000 HIV tests at the national level.

Blood was collected for HIV testing from all consenting ever-married and never married women age 15-49 and men age 15-54 in all sample households in Andhra Pradesh, Karnataka, Maharashtra, Manipur, Tamil Nadu, and Uttar Pradesh. All women age 15-49 and men age 15-54 in the sample households were eligible for interviewing in all of these states plus Nagaland. In the remaining 22 states, all ever-married and never married women age 15-49 in sample households were eligible to be interviewed. In those 22 states, men age 15-54 were eligible to be interviewed in only a subsample of households. HIV tests for women and men were carried out in only a subsample of the households that were selected for men's interviews in those 22 states. The reason for this sample design is that the required number of HIV tests is determined by the need to calculate HIV prevalence at the national level and for some states, whereas the number of individual interviews is determined by the need to provide state level estimates for attitudinal and behavioural indicators in every state. For statistical reasons, it is not possible to estimate HIV prevalence in every state from NFHS-3 as the number of tests required for estimating HIV prevalence reliably in low HIV prevalence states would have been very large.

SAMPLE DESIGN

The urban and rural samples within each state were drawn separately and, to the extent possible, unless oversampling was required to permit separate estimates for urban slum and non-slum areas, the sample within each state was allocated proportionally to the size of the state's urban and rural populations. A uniform sample design was adopted in all states. In each state, the rural sample was selected in two stages, with the selection of Primary Sampling Units (PSUs), which are villages, with probability proportional to population size (PPS) at the first stage, followed by the random selection of households within each PSU in the second stage. In urban areas, a three-stage procedure was followed. In the first stage, wards were selected with PPS sampling. In the next stage, one census enumeration block (CEB) was randomly selected from each sample ward. In the final stage, households were randomly selected within each selected CEB.

SAMPLE SELECTION IN RURAL AREAS

In rural areas, the 2001 Census list of villages served as the sampling frame. The list was stratified by a number of variables. The first level of stratification was geographic, with districts being subdivided into contiguous regions. Within each of these regions, villages were further stratified using selected variables from the following list: village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. In addition to these variables, an external estimate of HIV prevalence, i.e., 'High', 'Medium' or 'Low', as estimated for all the districts in high HIV prevalence states, was used for stratification in high HIV prevalence states. Female literacy was used for implicit stratification (i.e., villages were

The statistic displays the literacy rate in rural and urban regions of the state of Uttar Pradesh in India in 2011, with a breakdown by gender. In that year, the literacy rate among males living in rural areas in Uttar Pradesh was around 76 percent. India's literacy rate from 1981 through 2011 can be found here.

As per the Indian census data of 2011, about 83 percent of the male population in the southern state of Karnataka knew how to read or write. During the same year, the female literacy rate was at 68 percent in the state.

The 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 born in the three years preceding NFHS-2 received at least one antenatal

Abstract

The National Family Health Survey 2019-21 (NFHS-5), the fifth in the NFHS series, provides information on population, health, and nutrition for India, each state/union territory (UT), and for 707 districts.

The primary objective of the 2019-21 round of National Family Health Surveys is to provide essential data on health and family welfare, as well as data on emerging issues in these areas, such as levels of fertility, infant and child mortality, maternal and child health, and other health and family welfare indicators by background characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, noncommunicable diseases, and the use of emergency contraception.

The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas.

The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 54

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-54, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs.

For further details on sample design, see Section 1.2 of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four survey schedules/questionnaires: Household, Woman, Man, and Biomarker were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI).

Cleaning operations

Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized.

Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required.

Response rate

A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent.

In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent.

Financial Inclusion (FI) is one of the most important indicators of inclusive growth of an economy. This paper examines the status of FI in India by constructing a comprehensive financial inclusion index (FII). The data analysis indicates that states such as Goa, Kerala, Tamil Nadu, Maharashtra, and Telangana performed well in FI. Further, a panel data regression model is estimated to know the determinants of financial inclusion in 27 Indian States for the period 2005 to 2020. The composite index can be used to monitor and assess financial inclusion over time and at the grass root level also. The estimated results show that per capita NSDP, literacy rate, urban population share, road length, and number of factories are perhaps the most important financial inclusion determinants. The novelty of this study is to provide a comprehensive understanding of financial inclusion levels across different states in India for two-decade period along with rural and urban financial inclusion levels. The study serves as a critical resource for understanding the dynamics of financial inclusion in India for the two decades period and offers valuable insights for policymakers by identifying key determinants and guide the development of targeted policies aimed at improving financial inclusion, which is essential for economic growth and development.

Abstract

The National Family Health Survey (NFHS) was carried out as the principal activity of a collaborative project to strengthen the research capabilities of the Population Reasearch Centres (PRCs) in India, initiated by the Ministry of Health and Family Welfare (MOHFW), Government of India, and coordinated by the International Institute for Population Sciences (IIPS), Bombay. Interviews were conducted with a nationally representative sample of 89,777 ever-married women in the age group 13-49, from 24 states and the National Capital Territoty of Delhi. The main objective of the survey was to collect reliable and up-to-date information on fertility, family planning, mortality, and maternal and child health. Data collection was carried out in three phases from April 1992 to September 1993. THe NFHS is one of the most complete surveys of its kind ever conducted in India.

The households covered in the survey included 500,492 residents. The young age structure of the population highlights the momentum of the future population growth of the country; 38 percent of household residents are under age 15, with their reproductive years still in the future. Persons age 60 or older constitute 8 percent of the population. The population sex ratio of the de jure residents is 944 females per 1,000 males, which is slightly higher than sex ratio of 927 observed in the 1991 Census.

The primary objective of the NFHS is to provide national-level and state-level data on fertility, nuptiality, family size preferences, knowledge and practice of family planning, the potentiel demand for contraception, the level of unwanted fertility, utilization of antenatal services, breastfeeding and food supplemation practises, child nutrition and health, immunizations, and infant and child mortality. The NFHS is also designed to explore the demographic and socioeconomic determinants of fertility, family planning, and maternal and child health. This information is intended to assist policymakers, adminitrators and researchers in assessing and evaluating population and family welfare programmes and strategies. The NFHS used uniform questionnaires and uniform methods of sampling, data collection and analysis with the primary objective of providing a source of demographic and health data for interstate comparisons. The data collected in the NFHS are also comparable with those of the Demographic and Health Surveys (DHS) conducted in many other countries.

Geographic coverage

National

Analysis unit

• Household
• Data collected for women 13-49, indicators calculated for women 15-49

Universe

The population covered by the 1992-93 DHS is defined as the universe of all women age 13-49 who were either permanent residents of the households in the NDHS sample or visitors present in the households on the night before the survey were eligible to be interviewed.

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN

The sample design for the NFHS was discussed during a Sample Design Workshop held in Madurai in Octber, 1991. The workshop was attended by representative from the PRCs; the COs; the Office of the Registrar General, India; IIPS and the East-West Center/Macro International. A uniform sample design was adopted in all the NFHS states. The Sample design adopted in each state is a systematic, stratified sample of households, with two stages in rural areas and three stages in urban areas.

SAMPLE SIZE AND ALLOCATION

The sample size for each state was specified in terms of a target number of completed interviews with eligible women. The target sample size was set considering the size of the state, the time and ressources available for the survey and the need for separate estimates for urban and rural areas of the stat. The initial target sample size was 3,000 completed interviews with eligible women for states having a population of 25 million or less in 1991; 4,000 completed interviews for large states with more than 25 million population; 8,000 for Uttar Pradesh, the largest state; and 1,000 each for the six small northeastern states. In States with a substantial number of backward districts, the initial target samples were increased so as to allow separate estimates to be made for groups of backward districts.

The urban and rural samples within states were drawn separetly and , to the extent possible, sample allocation was proportional to the size of the urban-rural populations (to facilitate the selection of a self-weighting sample for each state). In states where the urban population was not sufficiently large to provide a sample of at least 1,000 completed interviews with eligible women, the urban areas were appropriately oversampled (except in the six small northeastern states).

THE RURAL SAMPLE: THE FRAME, STRATIFICATION AND SELECTION

A two-stage stratified sampling was adopted for the rural areas: selection of villages followed by selection of households. Because the 1991 Census data were not available at the time of sample selection in most states, the 1981 Census list of villages served as the sampling frame in all the states with the exception of Assam, Delhi and Punjab. In these three states the 1991 Census data were used as the sampling frame.

Villages were stratified prior to selection on the basis of a number of variables. The firts level of stratification in all the states was geographic, with districts subdivided into regions according to their geophysical characteristics. Within each of these regions, villages were further stratified using some of the following variables : village size, distance from the nearest town, proportion of nonagricultural workers, proportion of the population belonging to scheduled castes/scheduled tribes, and female literacy. However, not all variables were used in every state. Each state was examined individually and two or three variables were selected for stratification, with the aim of creating not more than 12 strata for small states and not more than 15 strata for large states. Females literacy was often used for implicit stratification (i.e., the villages were ordered prior to selection according to the proportion of females who were literate). Primary sampling Units (PSUs) were selected systematically, with probaility proportional to size (PPS). In some cases, adjacent villages with small population sizes were combined into a single PSU for the purpose of sample selection. On average, 30 households were selected for interviewing in each selected PSU.

In every state, all the households in the selected PSUs were listed about two weeks prior to the survey. This listing provided the necessary frame for selecting households at the second sampling stage. The household listing operation consisted of preparing up-to-date notional and layout sketch maps of each selected PSU, assigning numbers to structures, recording addresses (or locations) of these structures, identifying the residential structures, and listing the names of the heads of all the households in the residentiak structures in the selected PSU. Each household listing team consisted of a lister and a mapper. The listing operation was supervised by the senior field staff of the concerned CO and the PRC in each state. Special efforts were made not to miss any household in the selected PSU during the listing operation. In PSUs with fewer than 500 households, a complete household listing was done. In PSUs with 500 or more households, segmentation of the PSU was done on the basis of existing wards in the PSU, and two segments were selected using either systematic sampling or PPS sampling. The household listing in such PSUs was carried out in the selected segments. The households to be interviewed were selected from provided with the original household listing, layout sketch map and the household sample selected for each PSU. All the selected households were approached during the data collection, and no substitution of a household was allowed under any circumstances.

THE RURAL URBAN SAMPLE: THE FRAME, STRATIFICATION AND SELECTION

A three-stage sample design was adopted for the urban areas in each state: selection of cities/towns, followed by urban blocks, and finally households. Cities and towns were selected using the 1991 population figures while urban blocks were selected using the 1991 list of census enumeration blocks in all the states with the exception of the firts phase states. For the first phase states, the list of urban blocks provided by the National Sample Survey Organization (NSSSO) served as the sampling frame.

All cities and towns were subdivided into three strata: (1) self-selecting cities (i.e., cities with a population large enough to be selected with certainty), (2) towns that are district headquaters, and (3) other towns. Within each stratum, the cities/towns were arranged according to the same kind of geographic stratification used in the rural areas. In self-selecting cities, the sample was selected according to a two-stage sample design: selection of the required number of urban blocks, followed by selection of households in each of selected blocks. For district headquarters and other towns, a three stage sample design was used: selection of towns with PPS, followed by selection of two census blocks per selected town, followed by selection of households from each selected block. As in rural areas, a household listing was carried out in the selected blocks, and an average of 20 households per block was selected systematically.

Mode of data collection

Face-to-face

Research instrument

Three types of questionnaires were used in the NFHS: the Household Questionnaire, the Women's Questionnaire, and the Village Questionnaire. The overall content

Abstract

The National Sample Survey Organisation (NSSO) carried out the first country wide comprehensive survey of physically disabled persons during the 36th round survey (July - December, 1981). The next survey on the subject was carried out after a period of ten years in NSS 47th round (July - December, 1991). In NSS 36th and 47th round surveys, information was collected on three types of physical disabilities - visual, communication and locomotor - along with the cause of disability, aid/appliance acquired by the disabled, general and vocational educational level of the disabled etc. In addition, data on developmental milestones and behavioural pattern of all children of age 5-14 years, regardless of whether they were physically disabled or not, were collected.

The Ministry of Social Justice and Empowerment (MSJE) made a request for conducting a survey on disability in order to meet the data needs for evolving specific strategies and interventions during the 10th Five Year Plan. The need for a detailed survey on disability was strongly felt by MSJE since its data requirement included not only the number of disabled persons, but also the socio-economic characteristics of the disabled persons such as their age structure, literacy, vocational training, employment, causative factors of disability, age at the onset of disability etc. Keeping in view the urgent data need of the MSJE, the Governing Council of NSSO, in its 81st meeting, decided that the survey on disability may also be carried out as a part of NSS 58th round during July - December 2002. It has been decided that: (i) The survey of disabled persons will also cover persons with mental disability apart from the physically disabled persons since the Ministry of Social Justice and Empowerment (MSJE) also requested for information on mentally disabled persons. The decision to include mental disability in the survey has been taken on the basis of a pre-test of the questions on mental disability, both for the listing and detailed schedules, carried out in the four cities of Kolkata, Mumbai, Hyderabad and Delhi.

(ii) The information for different types of disabilities is to be collected for persons of all age-groups. Separate information on the developmental milestones of children will not be collected.

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design

Outline of Sample Design

A stratified multi-stage design was adopted for the conduct of survey of NSS 58th round. The first-stage units were census villages (panchayat wards for Kerala) in the rural sector and the NSSO Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units were households in both the sectors.

Sampling Frame for First-Stage Units

For the rural sector, the list of Census 1991 villages (panchayat wards for Kerala) and Census 1981 villages for J & K constituted the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks was considered as the sampling frame.

Stratification

Rural sector: Two special strata were formed as given below at the State/ UT level on the basis of Population Census 1991 viz. Stratum 1: all FSUs with population between 0 to 50, and Stratum 2: FSUs with population more than 15,000 The special stratum 1 was formed if at least 50 such FSU's were found in a State/UT. Similarly, special stratum 2 was formed if at least 4 such FSUs were found in a State/UT. Otherwise, such FSUs were merged with the general strata. From the remaining FSUs (not covered under stratum 1 &2) general strata (hereafter, stratum will refer to general stratum unless otherwise mentioned) was formed and numbered 3, 4, 5 …. etc. (even if no special strata have been formed). Each district of a State/UT was normally treated as a separate stratum. However, if the provisional population of the district was greater than or equal to 2.5 million as per Census 2001, the district was divided into two or more strata with more or less equal population as per population census 1991 by grouping contiguous tehsils. However, in Gujarat, some districts were not wholly included in an NSS region. In such cases, the part of the district falling in an NSS region constituted a separate stratum.

Urban sector: In the urban sector, stratum was formed within each NSS region on the basis of size class of towns as per Census 1991 town population except for towns specified in Table 4. The stratum number and their composition (within each region) are given below: stratum 1: all towns with population (P) < 0.1 million
stratum 2: all towns with 0.1= P < 0.5 million
stratum 3: all towns with 0.5= P < 1 million
stratum 4,5,6, … each town with P= 1 million
The stratum numbers was retained as above even if, in some regions, some of the stratum is not formed.

Sub-stratification

There was no sub-stratification in the rural sector. However, to cover more number of households living in slums, in urban sector each stratum was divided into 2 sub-strata as follows: sub-stratum 1: all UFS blocks having area type 'slum area' sub-stratum 2: remaining UFS blocks If there was one UFS block with area type 'slum area' within a stratum, sub-stratum 1 was not formed; it was merged with sub-stratum 2.

Total sample size (FSUs)

A total number of 8338 and 9076 first-stage units were selected for survey in the Central and State samples respectively.

Allocation of total sample to States and UTs

The total sample FSUs was allocated to the States and UTs in proportion to provisional population as per Census 2001 subject to the availability of investigators ensuring more or less uniform work-load.

Allocation of State/ UT level sample to Rural and Urban sectors

State/UT level sample was allocated between two sectors in proportion to provisional population as per Census 2001 with double weightage to urban sector.

Allocation of Rural /Urban sector level sample size to strata / sub-strata

Both rural and urban sector samples allotted to a State/UT were allocated to different strata in proportion to population of the stratum. All the stratum-level allocations were adjusted to multiple of 2. Stratum-level sample size in the urban sector was further allocated to 2 sub-strata in proportion to the number of UFS blocks in them with double weightage to sub-stratum 1 subject to a minimum sample size of 2 or 4 to sub-stratum 1 according as stratum-level allocation is 4 or greater than 4. Sub-stratum level allocations in the urban sector were made even.

Selection of FSUs

FSUs were selected in the form of two independent sub-samples in both the sectors. For special stratum 2 and all the general strata of rural sector, FSUs were selected by probability proportional to size with replacement (PPSWR) where size was the 1991 census population. For urban sector and special stratum 1 of rural sector, FSUs were selected by simple random sampling without replacement (SRSWOR).

Selection of hamlet-groups/sub-blocks / households

Formation of hamlet-group/sub-block

Large villages/ blocks having approximate present population 1200 or more were divided into a suitable number of hamlet-groups/sub-blocks as given below: approximate present population no. of hamlet-groups/ sub-blocks formed
less than 1200 1 (no hamlet-group/sub-block formation)
1200 to 1799 3
1800 to 2399 4
2400 to 2999 5
3000 to 3599 6
....and so on

For rural areas of Himachal Pradesh, Sikkim and Poonch, Rajouri, Udhampur and Doda districts of Jammu and Kashmir and Idukki district of Kerala where habitation pattern causes difficulty in listing due to topography of the area, hg formation criterion was relaxed for which number of hamlet groups formed as per population criterion is given below: approximate present population no. of hamlet-groups/ sub-blocks formed
less than 600 1 (no hamlet-group/sub-block formation)
600 to 899 3
900 to 1199 4
1200 to 1499 5
....and so on

Hamlet-groups / sub-blocks were formed by more or less equalising population. For large urban blocks, the sub-block (sb) having slum dwellers, if any, was selected with probability 1 and was termed as segment 1. However, if there were more than one sb having slum dwellers, the sb having maximum number of slum dwellers was selected as segment 1. After selection of sb for segment 1, one more sb was selected by simple random sampling (SRS) from the remaining sb's of the block and was termed as segment 2. For large blocks (having no slum areas) two sub-blocks were selected by simple random sampling without replacement (SRSWOR) and were combined to form segment 2. For urban blocks without sub-block formation, segment number was 1 or 2 depending on whether the block was having a slum or not. For large villages two hamlet-groups were selected by SRSWOR and were combined to form segment 2. For villages without hamlet-group formation, segment number was also 2. The segments were considered separately for listing and selection of the ultimate-stage units.

Formation of Second Stage Strata (SSS) and selection of households for schedule 26

In each selected village/block/segment, three second stage strata (SSS) were formed on the basis of disability type. The number of households selected is given below: Without segment formation with segment formation (for each segment)

SSS 1: households

The statistic displays the literacy rate in the state of Assam in India between 1991 and 2011, by gender. In 2001, the literacy rate among female population living in Assam was around ** percent. India's literacy rate from 1981 through 2011 can be found here.

description: The National Indian Education Study, 2005 (NIES 2005), is a study that is part of the National Indian Education Study (NIES), which is a part of National Assessment of Educational Progress (NAEP) program; program data is available since 2005 at https://nces.ed.gov/nationsreportcard/nies/. NIES 2005 (https://nces.ed.gov/nationsreportcard/nies/) is a cross-sectional survey that is designed to describe the condition of education for American Indian and Alaska Native (AI/AN) students in the United States. Students in public, private, Department of Defense, and Bureau of Indian Education-funded schools were sampled using paper-and-pencil assessment in April and May of 2005. Overall weighted response rate for 4th grade reading was 83 percent. Overall weighted response rate for 8th grade reading was 85 percent. Overall weighted response rate for 4th grade math was 86 percent. Overall weighted response rate for 8th grade math was 87 percent. Key statistics produced from NIES 2005 provides educators, policymakers, and the public with information about the academic performance in reading and mathematics of AI/AN fourth- and eighth-graders as well as their exposure to Native American culture.; abstract: The National Indian Education Study, 2005 (NIES 2005), is a study that is part of the National Indian Education Study (NIES), which is a part of National Assessment of Educational Progress (NAEP) program; program data is available since 2005 at https://nces.ed.gov/nationsreportcard/nies/. NIES 2005 (https://nces.ed.gov/nationsreportcard/nies/) is a cross-sectional survey that is designed to describe the condition of education for American Indian and Alaska Native (AI/AN) students in the United States. Students in public, private, Department of Defense, and Bureau of Indian Education-funded schools were sampled using paper-and-pencil assessment in April and May of 2005. Overall weighted response rate for 4th grade reading was 83 percent. Overall weighted response rate for 8th grade reading was 85 percent. Overall weighted response rate for 4th grade math was 86 percent. Overall weighted response rate for 8th grade math was 87 percent. Key statistics produced from NIES 2005 provides educators, policymakers, and the public with information about the academic performance in reading and mathematics of AI/AN fourth- and eighth-graders as well as their exposure to Native American culture.

This dataset tracks annual reading and language arts proficiency from 2021 to 2022 for American Indian Academy Of Denver vs. Colorado and School District No. 1 In The County Of Denver And State Of C