Literacy Rate: Delhi data was reported at 86.200 % in 12-01-2011. This records an increase from the previous number of 81.670 % for 12-01-2001. Literacy Rate: Delhi data is updated decadal, averaging 73.615 % from Dec 1961 (Median) to 12-01-2011, with 6 observations. The data reached an all-time high of 86.200 % in 12-01-2011 and a record low of 61.950 % in 12-01-1961. Literacy Rate: Delhi 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.

The statistic depicts the literacy rate in Delhi in India between 1991 and 2011, broken down by gender. In 2001, ** percent of the male population living in Delhi knew how to read or write. India's literacy rate from 1981 through 2011 can be found here.

The statistic displays the literacy rate in rural and urban regions of Delhi in India in 2011, with a breakdown by gender. In that year, the literacy rate among females living in rural areas in Delhi was around 73 percent. India's literacy rate from 1981 through 2011 can be found here.

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.

Literacy Rate: NCT of Delhi在12-01-2011达86.200%，相较于12-01-2001的81.670%有所增长。Literacy Rate: NCT of Delhi数据按decadal更新，12-01-1961至12-01-2011期间平均值为73.615%，共6份观测结果。该数据的历史最高值出现于12-01-2011，达86.200%，而历史最低值则出现于12-01-1961，为61.950%。CEIC提供的Literacy Rate: NCT of Delhi数据处于定期更新的状态，数据来源于Office of the Registrar General & Census Commissioner, India，数据归类于India Premium Database的Education Sector – Table IN.EDA001: Literacy Rate。

Literacy Rate: Lakshadweep data was reported at 91.800 % in 12-01-2011. This records an increase from the previous number of 86.660 % for 12-01-2001. Literacy Rate: Lakshadweep data is updated decadal, averaging 68.420 % from Dec 1951 (Median) to 12-01-2011, with 7 observations. The data reached an all-time high of 91.800 % in 12-01-2011 and a record low of 15.230 % in 12-01-1951. Literacy Rate: Lakshadweep 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

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for village level demographic analysis within basic applications to support graphical overlays and analysis with other spatial data.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for village level demographic analysis within basic applications to support graphical overlays and analysis with other spatial data.

The Multilingualism and Multiliteracy (MultiLila) project was a four-year research study (2016 –2020).It aimed to examine whether a match or mismatch between the child’s home language(s) and the school language affect learning outcomes while at the same time taking into other factors that can affect a child’s performance on basic school skills and more advanced, problem-solving and reasoning skills. Specifically, socioeconomic status, school site, urban vs. rural location and differences between two urban sites (Delhi and Hyderabad) were considered when evaluating learning outcomes in the project’s tasks. The project also sought to understand whether children who use more than one language in the home or children who live in linguistically highly diverse environments have better cognitive skills than children in monolingual or less diverse contexts. A variety of quantitative and qualitative data were collected over a period of four years. The data include children’s performance on the fourteen different tasks of literacy, numeracy, oral language, verbal reasoning, and cognitive tasks mentioned above. In addition, we collected data from the surveys and questionnaires used for teacher and head-teacher interviews.

This innovative project examines the causes of low educational outcomes in schools in India where many children fail to achieve basic literacy and numeracy levels, while dropout rates, affecting girls more than boys, are very high. A starting point of this research is that bilingualism and multilingualism have revealed cognitive advantages and good learning skills in children raised in western societies. Multilingualism is the norm in India. However, rather than enjoying cognitive and learning advantages, multilingual Indian children show low levels of basic learning skills including critical thinking and problem-solving. This project is innovative in seeking to disentangle the causes of this paradox. The project builds on Tsimpli's large scale (600K) EU-funded THALES bilingualism project which assessed cognitive and language abilities of 700+ children in five different countries, expanding this project into numeracy, critical thinking and problem solving in multilingual children which are key elements in the Indian context. The PI and co-Is have been preparing this application for the last two years in conjunction with the current project partners and consultants in India with 20k. funding from the British Council and 3k funding from the Centre for Literacy and Multilingualism at the University of Reading. The PI was invited to take part in a Roundtable discussion on Multilingual Education at the British Council in September 2014 (https://www.youtube.com/watch?v=JXMhAzgcdzM).The applicants discussed key questions from charities and schools and obtained advice from a range of educational and linguistics experts in Delhi and Hyderabad and visited different schools in both cities in 2014-15. The key question this project seeks to address is to explore how the complex dynamics of social, economic and geographical contexts affect the delivery of quality multilingual education in India. The growth of literacy and numeracy in children is constrained by complex interactions between elements of the education system, the context in which they are embedded, and the dynamics operating within that system. By conducting research among children living in urban slums in Delhi and Hyderabad as well as in remote rural areas of Bihar where food deprivation, low sanitation, poverty and migration make school attendance and education hard to maintain, the project focuses on structural and language inequalities affecting educational quality in India. Language inequalities arise because a large number of children in India are deprived of receiving mother-tongue support, being instructed only in the regional language and English, often from teachers with poor teaching qualifications and practices or limited knowledge of the language of instruction too. Teaching practices in India are teacher- and textbook-centred with detrimental effects on the development of critical thinking and problem solving abilities. These skills are fundamental in every learning process including numeracy and the understanding of mathematics. The method of this study is highly innovative in a number of ways. A combination of several tasks and questionnaires will address the role of several factors on learning outcomes. Each child's language, literacy and numeracy skills will be evaluated at two time points with a one year interval between them. This design is known to provide reliable findings on the development of learning rather than only on knowledge itself allowing future interventions to build on these findings to ensure improved outcomes. This study will provide policymakers and practitioners with concrete ideas on how to improve learning outcomes in the multilingual education context of India. It will offer a crucial understanding of...

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