Turkey TR: Educational Attainment: At Least Completed Primary: Population 25+ Years: Female: % Cumulative data was reported at 82.007 % in 2015. This records an increase from the previous number of 81.458 % for 2014. Turkey TR: Educational Attainment: At Least Completed Primary: Population 25+ Years: Female: % Cumulative data is updated yearly, averaging 76.363 % from Dec 2004 (Median) to 2015, with 12 observations. The data reached an all-time high of 82.007 % in 2015 and a record low of 68.543 % in 2006. Turkey TR: Educational Attainment: At Least Completed Primary: Population 25+ Years: Female: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed primary education.; ; UNESCO Institute for Statistics; ;

The dataset contains the education data listed on the website of Turkish Statistical Institute. Link: https://data.tuik.gov.tr/Kategori/GetKategori?p=Egitim,-Kultur,-Spor-ve-Turizm-105

Compulsary education system was changed in Turkey in 1997 from 5 years to 8 years. The "Primary School" column in the dataset refers to the population who graduated through the old education system.

Turkey TR: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data was reported at 1.756 % in 2015. This records an increase from the previous number of 1.636 % for 2014. Turkey TR: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 1.636 % from Dec 2013 (Median) to 2015, with 3 observations. The data reached an all-time high of 1.756 % in 2015 and a record low of 1.553 % in 2013. Turkey TR: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed Master's or equivalent.; ; UNESCO Institute for Statistics; ;

The 1993 Turkish Demographic and Health Survey (TDHS) is a nationally representative survey of ever-married women less than 50 years old. The survey was designed to provide information on fertility levels and trends, infant and child mortality, family planning, and maternal and child health. The TDHS was conducted by the Hacettepe University Institute of Population Studies under a subcontract through an agreement between the General Directorate of Mother and Child Health and Family Planning, Ministry of Health and Macro International Inc. of Calverton, Maryland. Fieldwork was conducted from August to October 1993. Interviews were carried out in 8,619 households and with 6,519 women. The Turkish Demographic and Health Survey (TDHS) is a national sample survey of ever-married women of reproductive ages, designed to collect data on fertility, marriage patterns, family planning, early age mortality, socioeconomic characteristics, breastfeeding, immunisation of children, treatment of children during episodes of illness, and nutritional status of women and children. The TDHS, as part of the international DHS project, is also the latest survey in a series of national-level population and health surveys in Turkey, which have been conducted by the Institute of Population Studies, Haeettepe University (HIPS). More specifically, the objectives of the TDHS are to: Collect data at the national level that will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; Analyse the direct and indirect factors that determine levels and trends in fertility and childhood mortality; Measure the level of contraceptive knowledge and practice by method, region, and urban- rural residence; Collect data on mother and child health, including immunisations, prevalence and treatment of diarrhoea, acute respiratory infections among children under five, antenatal care, assistance at delivery, and breastfeeding; Measure the nutritional status of children under five and of their mothers using anthropometric measurements. The TDHS information is intended to assist policy makers and administrators in evaluating existing programs and in designing new strategies for improving family planning and health services in Turkey. MAIN RESULTS Fertility in Turkey is continuing to decline. If Turkish women maintain current fertility rates during their reproductive years, they can expect to have all average of 2.7 children by the end of their reproductive years. The highest fertility rate is observed for the age group 20-24. There are marked regional differences in fertility rates, ranging from 4.4 children per woman in the East to 2.0 children per woman in the West. Fertility also varies widely by urban-rural residence and by education level. A woman living in rural areas will have almost one child more than a woman living in an urban area. Women who have no education have almost one child more than women who have a primary-level education and 2.5 children more than women with secondary-level education. The first requirement of success ill family planning is the knowledge of family planning methods. Knowledge of any method is almost universal among Turkish women and almost all those who know a method also know the source of the method. Eighty percent of currently married women have used a method sometime in their life. One third of currently married women report ever using the IUD. Overall, 63 percent of currently married women are currently using a method. The majority of these women are modern method users (35 percent), but a very substantial proportion use traditional methods (28 percent). the IUD is the most commonly used modern method (I 9 percent), allowed by the condom (7 percent) and the pill (5 percent). Regional differences are substantial. The level of current use is 42 percent in tile East, 72 percent in tile West and more than 60 percent in tile other three regions. "File common complaints about tile methods are side effects and health concerns; these are especially prevalent for the pill and IUD. One of the major child health indicators is immunisation coverage. Among children age 12-23 months, the coverage rates for BCG and the first two doses of DPT and polio were about 90 percent, with most of the children receiving those vaccines before age one. The results indicate that 65 percent of the children had received all vaccinations at some time before the survey. On a regional basis, coverage is significantly lower in the Eastern region (41 percent), followed by the Northern and Central regions (61 percent and 65 percent, respectively). Acute respiratory infections (ARI) and diarrhea are the two most prevalent diseases of children under age five in Turkey. In the two weeks preceding the survey, the prevalence of ARI was 12 percent and the prevalence of diarrhea was 25 percent for children under age five. Among children with diarrhea 56 percent were given more fluids than usual. Breastfeeding in Turkey is widespread. Almost all Turkish children (95 percent) are breastfed for some period of time. The median duration of breastfeeding is 12 months, but supplementary foods and liquids are introduced at an early age. One-third of children are being given supplementary food as early as one month of age and by the age of 2-3 months, half of the children are already being given supplementary foods or liquids. By age five, almost one-filth of children arc stunted (short for their age), compared to an international reference population. Stunting is more prevalent in rural areas, in the East, among children of mothers with little or no education, among children who are of higher birth order, and among those born less than 24 months after a prior birth. Overall, wasting is not a problem. Two percent of children are wasted (thin for their height), and I I percent of children under five are underweight for their age. The survey results show that obesity is d problem among mothers. According to Body Mass Index (BMI) calculations, 51 percent of mothers are overweight, of which 19 percent are obese.

Description of variables in the file: Cities contains 36 cities of Turkey. College_graduate contains the percentage of people who have at least a college degree or equivalent. High_school_graduate contains the percentage of people who have at least a high school diploma or equivalent. Less_than_high_school contains the percentage of people who are less educated than high school level. COVID-19_Vaccination contains the vaccination percentage of cities. Unvaccinated contains the percentage of unvaccinated people. In this work, we investigated the correlation between education levels and COVID-19 vaccination in 36 cities in Turkey. We demonstrated if the percentage of people less educated than high school level increases, the percentage of unvaccinated people increases too. The correlation value between the percentage of people less educated than high school level and the percentage of unvaccinated people is 0.9198. The methods used are correlation matrix and linear regression. Education levels data are collected from Turkish Statistical Institute, and vaccination percentage of the cities data are collected from the national public broadcaster of Turkey, Turkish Radio and Television Corporation.

Turkey TR: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Total: % Cumulative data was reported at 56.355 % in 2015. This records an increase from the previous number of 54.968 % for 2014. Turkey TR: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 34.920 % from Dec 1975 (Median) to 2015, with 15 observations. The data reached an all-time high of 56.355 % in 2015 and a record low of 9.100 % in 1975. Turkey TR: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Total: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed lower secondary education.; ; UNESCO Institute for Statistics; ;

Introduction

Welcome to the English-Turkish Bilingual Parallel Corpora dataset for the Education domain! This comprehensive dataset contains a vast collection of bilingual text data, carefully translated between English to Turkish, to support the development of Education-specific language models and machine translation engines.

Dataset Content

Domain Specific Content

This Parallel Corpus is meticulously curated to capture the linguistic intricacies and domain-specific nuances inherent to the Education industry.

Format and Structure

Usage and Application

We created a dataset involving 57 students from Diyarbakır Kokulupinar primary school in Turkey. The Social and Human Sciences Research Ethics Committee, Firat University, Turkey approved the study. The classroom teacher, who voluntarily supported the study, identified fifty-eight students at their school who they considered to have good, average, and poor reading skills. The parents of these students were contacted about the study by the study investigators via telephone, to explain the study and obtain permission. The voluntary nature of the study was explained. All parents agreed to their child's participation, although one parent subsequently asked to withdraw his child from the study. The study included 28 female and 29 male students, whose ages varied between 8 and 11 (the average age is 10.15). The reading levels and genders of the students are given below.

Details of the collected dataset. Reading Level Female Male Total Bad 3 15 18 Good 14 5 19 Intermediate 11 9 20 Grand Total 28 29 57

The study population has been tabulated in Table 1, and a fixed/standard paragraph was used to detect the reading level of the participants. A standard reading text is given in Appendix. Moreover, the teachers of these students made labeling and we validated these labels according to their reading points. We got permission from parents (we called the participants' parents and gave information about this scientific research). The collected speech files were split into separate files for each sentence. While naming the resulting files, sequential and underscore character distinction was used in the form of reading level, person ID, and file ID. The audio files were listened by three different teachers independently, blinded to each child's name. Each sentence was labeled according to the reading level. Some students read some sentences well and others poorly. For this reason, the numbers in each class differed according to the reading level. The number of observations is shown below.

Number of observations by reading levels. Reading Level Observation Bad 402 Intermediate/Moderate 460 Good 437 Total 1299

In order to use the dataset here, the following article must be cited. - Abed, R.Q., Dikmen, M., Aydemir, E. et al. Automated reading level classification model based on improved orbital pattern. Multimed Tools Appl (2023). https://doi.org/10.1007/s11042-023-17535-8

Turkey TR: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data was reported at 0.283 % in 2015. This records an increase from the previous number of 0.275 % for 2014. Turkey TR: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data is updated yearly, averaging 0.275 % from Dec 2013 (Median) to 2015, with 3 observations. The data reached an all-time high of 0.283 % in 2015 and a record low of 0.268 % in 2013. Turkey TR: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank.WDI: Education Statistics. The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.; ; UNESCO Institute for Statistics; ;

-> If you use Turkish_Product_Reviews_by_Gozukara_and_Ozel_2016 dataset please cite: https://dergipark.org.tr/en/pub/cukurovaummfd/issue/28708/310341

@research article { cukurovaummfd310341, journal = {Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi}, issn = {1019-1011}, eissn = {2564-7520}, address = {Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi Yayın Kurulu Başkanlığı 01330 ADANA}, publisher = {Cukurova University}, year = {2016}, volume = {31}, pages = {464 - 482}, doi = {10.21605/cukurovaummfd.310341}, title = {Türkçe ve İngilizce Yorumların Duygu Analizinde Doküman Vektörü Hesaplama Yöntemleri için Bir Deneysel İnceleme}, key = {cite}, author = {Gözükara, Furkan and Özel, Selma Ayşe} }

https://doi.org/10.21605/cukurovaummfd.310341

-> Turkish_Product_Reviews_by_Gozukara_and_Ozel_2016 dataset is composed as below: ->-> Top 50 E-commerce sites in Turkey are crawled and their comments are extracted. Then randomly 2000 comments selected and manually labelled by a field expert. ->-> After manual labeling the selected comments is done, 600 negative and 600 positive comments are left. ->-> This dataset contains these comments.

-> English_Movie_Reviews_by_Pang_and_Lee_2004 ->-> Pang, B., Lee, L., 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts, In Proceedings of the 42nd annual meeting on Association for Computational Linguistics (p. 271). ->-> Source: https://www.cs.cornell.edu/people/pabo/movie-review-data/ | polarity dataset v2.0 - review_polarity.tar.gz

-> English_Movie_Reviews_Sentences_by_Pang_and_Lee_2005 ->-> Pang, B., Lee, L., 2005. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales, In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics (pp. 115-124), Association for Computational Linguistics ->-> Source: https://www.cs.cornell.edu/people/pabo/movie-review-data/ | sentence polarity dataset v1.0 - rt-polaritydata.tar.gz

-> English_Product_Reviews_by_Blitzer_et_al_2007 ->-> Article of the dataset: Blitzer, J., Dredze, M., Pereira, F., 2007. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification, In ACL (Vol. 7, pp. 440-447). ->-> Source: http://www.cs.jhu.edu/~mdredze/datasets/sentiment/ | processed_acl.tar.gz

-> Turkish_Movie_Reviews_by_Demirtas_and_Pechenizkiy_2013 ->-> Demirtas, E., Pechenizkiy, M., 2013. Cross-lingual polarity detection with machine translation, In Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining (p. 9). ACM. ->-> http://www.win.tue.nl/~mpechen/projects/smm/#Datasets Turkish_Movie_Sentiment.zip

-> The dataset files are provided as used in the article. -> Weka files are generated with Raw Frequency of terms rather than used Weighting Schemes

-> The folder Cross_Validation contains 10-fold cross-validation each fold files. -> Inside Cross_Validation folder, each turn of the cross-validation is named as test_X where X is the turn number -> Inside test_X folder * Test_Set_Negative_RAW: Contains raw negative class Test data of that cross-validation turn * Test_Set_Negative_Processed: Contains pre-processed negative class Test data of that cross-validation turn * Test_Set_Positive_RAW: Contains raw positive class Test data of that cross-validation turn * Test_Set_Positive_Processed: Contains pre-processed positive class Test data of that cross-validation turn * Train_Set_Negative_RAW: Contains raw negative class Train data of that cross-validation turn * Train_Set_Negative_Processed: Contains pre-processed negative class Train data of that cross-validation turn * Train_Set_Positive_RAW: Contains raw positive class Train data of that cross-validation turn * Train_Set_Positive_Processed: Contains pre-processed positive class Train data of that cross-validation turn * Train_Set_For_Weka: Contains processed Train set formatted for Weka * Test_Set_For_Weka: Contains processed Test set formatted for Weka

-> The folder Entire_Dataset contains files for Entire Dataset * Negative_Processed: Contains all negative comments processed data * Positive_Processed: Contains all positive comments processed data * Negative_RAW: Contains all negative comments RAW data * Positive_RAW: Contains all positive comments RAW data * Entire_Dataset_WEKA: Contains all documents processed data in WEKA format

Abstract

The Survey on Income and Living Conditions, introduced as part of the European Union harmonisation efforts, aims to produce data on income distribution, relative poverty by income, living conditions and social exclusion comparable with European Union member states. The study which uses a panel survey method is repeated every year and monitors sample of household members for four years. Every year, the study attempts to obtain two datasets: cross-sectional and panel.

The Income and Living Conditions Survey 2010 has been conducted to provide annual and regular cross-sectional data to answer questions such as:

• How equally is the income in the country distributed and how has it changed as compared to the previous years?
• How many poor people are there in the country and how do they distribute across regions? How has this situation changed as compared to the previous years?
• Who is poor? Has there been a change over time?
• How has this gap between the poor and the rich evolved over time?
• What kind of a change or transition occurs in the incomes of individuals and households? How does the direction of this change depends on characteristics and circumstances, does it decline or grow?
• How is the income distributed across sectors, types of income and household characteristics?
• How do people's living conditions change or improve over time?
• The study also aims to provide panel data to calculate indicators such as persistent income poverty and to measure net changes over time.

The cross-sectional database 2010 is documented here.

Geographic coverage

All settlements within the borders of the Republic of Turkey have been included.

Universe

All household members living in households within the borders of the Republic of Turkey. However, the study excludes the population defined as institutional population living in hospices, elderly homes, prisons, military barracks, private hospitals and in childcare centres. Migrant population has also been excluded due to practical challenges.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling method: Stratified, multi-stage, clustered sampling.

Sampling unit: Household.

Sampling framework: Sampling framework has been derived from 2 sources:

1. For the settlements with municipal status; General Building Census conducted in 2000 by TurkStat and Numbering Study (conducted in 2000) Form Population 1 data have been used.
2. For the settlements without municipal status (Villages); data of General Population Census conducted in 2000 have been used to select the blocks which constituted the sampling unit of the first stage.

Selection of sample households: for the purposes of the study which used a two-staged sampling design; entire Turkey has been divided into blocks which covered 100 households each.

• At the first stage, blocks were selected as the first stage sampling unit
• At the second stage, households were selected from among the previously selected blocks as the final sampling unit. Prior to the selection of sample households, addresses at the blocks were updated through an "address screening study"

Sample size: Annual sampling size is 13,414 households in respect of the estimation, objectives and targeted variables of the study and in consideration of the attritions in the sample.

Substitution principle: Substitution has not been used as the sample size had been calculated by taking account of non-response.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

• Household registry form: The form filled at the beginning of the survey provides brief information on access to the address of the household, condition of the household and of the survey. Moreover, following the first field application, modalities are identified for filling in the monitoring forms if the households included in the panel survey move home.

• Personal registry form: These forms aim to identify basic demographic characteristics of the household members, changes that occur in the status of household membership of the individuals included in the panel survey, reasons for their leaving the household, the date of their departure etc. as well as individuals who join the household.

• Household and personal follow-up form: There is need for following up the households which have moved home and the sample individuals who have left the household to join or found another one. Household and personal follow-up forms are used to identify their new addresses and access their contact information.

• Household questionnaire: These forms attempt to collect information on the type of the occupied dwelling, status of ownership, information relating to the dwelling (number of rooms, the space actually used, heating system, dwelling facilities, goods owned etc), problems of the dwelling of the neighbourhood, status of indebtedness, rent payments, expenditures for the dwelling, the extent to which households are able to meet their general economic and basic needs and incomes earned at household level.

• Personal questionnaire: These forms attempt to collect information on education, health, employment and marital status of the household members aged 15 and over, as well as the dates of employment and incomes earned during the reference year.

The data set includes the GIS coordination and population information of 18 potential service points (2 hospitals, 1 Red Crescent office, and 15 schools) together with 187 (109 villages and 78 neighbourhoods) main locations where Syrian refugees inhabit in the Kilis province in southern Turkey. Locations are classified as Villages (Köy) and Neighbourhoods (Mahalle) based on administrative divisions of Turkey. The population of each identified demand location, which is obtained from the local government in 2018, is provided as well.

The dataset has been used for a study on how to design a network of administrative facilities to support the roll-out of cash-based interventions, using refugee locations from the dataset to identify appropriate locations for these administrative facilities using the model presented in the paper. For decades the humanitarian sector has mainly relied on providing material assistance to beneficiaries during disaster relief. These days there is a growing importance in the provision of services, not only by means of replacing the distribution of relief items by cash & vouchers that can be exchanged for goods as needed but also in the provision of supporting services such as health or education. These services can help stimulate local market activity and restart livelihoods.

In this project we aim to design and implement the supply chain for two key services to beneficiaries: cash & voucher distribution (as a replacement for distributing core relief items).

The dataset has been used for a study on how to design a network of administrative facilities to support the roll-out of cash-based interventions, using refugee locations from the dataset to identify appropriate locations for these administrative facilities using the model presented in the paper.

Dataset

This dataset was created by Mehmet Emin Aydin

Contents

Context

The data set is taken from kemik group http://www.kemik.yildiz.edu.tr/ The data are pre-processed for the text categorization, collocations are found, character set is corrected, and so forth. We named TTC4900 by mimicking the name convention of TTC 3600 dataset shared by the study http://journals.sagepub.com/doi/abs/10.1177/0165551515620551

If you use the dataset in a paper, please refer https://www.kaggle.com/savasy/ttc4900 as footnote and cite one of the papers as follows:

• A Comparison of Different Approaches to Document Representation in Turkish Language, SDU Journal of Natural and Applied Science, Vol 22, Issue 2, 2018
• A comparative analysis of text classification for Turkish language, Pamukkale University Journal of Engineering Science Volume 25 Issue 5, 2018
• A Knowledge-poor Approach to Turkish Text Categorization with a Comparative Analysis, Proceedings of CICLING 2014, Springer LNCS, Nepal, 2014.

Content

Each row represents the documents, and the categories

Acknowledgements

Thanks to kemik group,

Inspiration

Text Categorization, BOW, LSI, Deep Learning Approaches are the techniques to be applied

The project 'Family and Working Life in the 21st Century' (YAPS) began in 1998. The aim was to establish a longitudinal database for studying the mutual relationship between values and demographic behavior. The values one holds influence how crucial decisions are made, such as moving in with a partner, having children, or changing jobs. The project analyzes both the significance of values for partnership formation and childbearing in early adulthood (up to 35 years of age) and how values regarding family and work change over time, depending on changes in family situation. To achieve this, panel data is required, meaning data from the same individuals at two or more points in time. This allows for distinguishing between selection and adaptation effects.

The first survey was conducted in the spring of 1999 and targeted individuals who were 22, 26, or 30 years old at the time of the survey. There were two different samples: one consisting of individuals with two Swedish-born parents, and one of individuals with one or both parents born in Poland or Turkey. A second survey round took place in the spring of 2003, when the respondents were four years older. The 2003 survey also included a new group of 22-year-olds in the Swedish sample. A third data collection was conducted in the spring of 2009.

In addition to variables collected through the surveys, a number of background variables were obtained from Statistics Sweden’s Total Population Register (RTB) and Education Register. These data refer to January 1999 and January 2003, respectively.

The response rate for the 1999 survey was 67% for the Swedish sample, 60% for respondents with a Polish background, and 49% for respondents with a Turkish background. In the 2003 survey, the response rate for the Swedish sample was 72%—78% for respondents who also participated in the 1999 survey and 60% for the new sample (born in 1980)—and for the second-generation sample, the response rate was 67% (69% for those with a Polish background and 65% for those with a Turkish background).

Turkey TR: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Male: % Cumulative data was reported at 2.076 % in 2015. This records an increase from the previous number of 1.957 % for 2014. Turkey TR: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Male: % Cumulative data is updated yearly, averaging 1.957 % from Dec 2013 (Median) to 2015, with 3 observations. The data reached an all-time high of 2.076 % in 2015 and a record low of 1.874 % in 2013. Turkey TR: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Male: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed Master's or equivalent.; ; UNESCO Institute for Statistics; ;

Turkey TR: Labour Force With Advanced Education: % of Total Working-age Population data was reported at 72.540 % in 2017. This records an increase from the previous number of 71.090 % for 2016. Turkey TR: Labour Force With Advanced Education: % of Total Working-age Population data is updated yearly, averaging 69.520 % from Dec 2006 (Median) to 2017, with 12 observations. The data reached an all-time high of 72.540 % in 2017 and a record low of 67.030 % in 2006. Turkey TR: Labour Force With Advanced Education: % of Total Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Labour Force. The percentage of the working age population with an advanced level of education who are in the labor force. Advanced education comprises short-cycle tertiary education, a bachelor’s degree or equivalent education level, a master’s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;

Turkey TR: Educational Attainment: At Least Competed Short-Cycle Tertiary: Population 25+ Years: Male: % Cumulative data was reported at 20.128 % in 2015. This records an increase from the previous number of 18.483 % for 2014. Turkey TR: Educational Attainment: At Least Competed Short-Cycle Tertiary: Population 25+ Years: Male: % Cumulative data is updated yearly, averaging 13.563 % from Dec 2004 (Median) to 2015, with 12 observations. The data reached an all-time high of 20.128 % in 2015 and a record low of 9.574 % in 2004. Turkey TR: Educational Attainment: At Least Competed Short-Cycle Tertiary: Population 25+ Years: Male: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed short-cycle tertiary education.; ; UNESCO Institute for Statistics; ;

Abstract

In 2010, the EU-SILC instrument covered 32 countries, that is, all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 6th version of the 2010 Cross-Sectional User Database as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Spain; Ireland; Italy; Latvia; Lithuania; Luxembourg; Hungary; Malta; Netherlands; Poland; Portugal; Romania; Slovenia; Slovakia; Sweden; United Kingdom; Iceland; Norway; Turkey; Switzerland

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

Turkey TR: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Total: % Cumulative data was reported at 0.339 % in 2015. This records a decrease from the previous number of 0.351 % for 2014. Turkey TR: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 0.344 % from Dec 2013 (Median) to 2015, with 3 observations. The data reached an all-time high of 0.351 % in 2014 and a record low of 0.339 % in 2015. Turkey TR: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Total: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.; ; UNESCO Institute for Statistics; ;