Relevant bibliographies by topics / Economic statistical control charts

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Economic statistical control charts'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Economic statistical control charts"

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Saraie, Ali. "Economic-statistical design of MC1 control charts." International Journal of Advanced Manufacturing Technology 32, no. 1-2 (2006): 157–61. http://dx.doi.org/10.1007/s00170-005-0306-4.

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Linderman, Kevin, and Thomas E. Love. "Economic and Economic Statistical Designs for MEWMA Control Charts." Journal of Quality Technology 32, no. 4 (2000): 410–17. http://dx.doi.org/10.1080/00224065.2000.11980026.

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Magalhães, Maysa Sacramento de, and Francisco Duarte Moura Neto. "Economic-statistical design of variable parameters non-central chi-square control chart." Production 21, no. 2 (2011): 259–70. http://dx.doi.org/10.1590/s0103-65132011005000031.

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Production processes are monitored by control charts since their inception by Shewhart (1924). This surveillance is useful in improving the production process due to increased stabilization of the process, and consequently standardization of the output. Control charts keep track of a few key quality characteristics of the outcome of the production process. This is done by means of univariate or multivariate charts. Small improvements in control chart methodology can have significant economic impact in the production process. In this investigation, we propose the monitoring of a single variable
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Katebi, Mehdi, Reza Poortaheri, and Mohammad Bameni Moghadam. "Economic and economic statistical designs for three-level control charts." Journal of Statistical Computation and Simulation 86, no. 8 (2015): 1463–78. http://dx.doi.org/10.1080/00949655.2015.1071373.

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Yu, Fong‐Jung, Hsiang Chin, and Hsiao Wei Huang. "An Economic‐Statistical Design of Moving Average Control Charts." Asian Journal on Quality 7, no. 3 (2006): 107–15. http://dx.doi.org/10.1108/15982688200600032.

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Saniga, Erwin M. "Economic Statistical Control-Chart Designs with an Application to X̄ and R Charts." Technometrics 31, no. 3 (1989): 313. http://dx.doi.org/10.2307/3556141.

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Dumičić, Ksenija, and Berislav Žmuk. "Statistical Control Charts: Performances of Short Term Stock Trading in Croatia." Business Systems Research Journal 6, no. 1 (2015): 22–35. http://dx.doi.org/10.1515/bsrj-2015-0002.

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Abstract Background: The stock exchange, as a regulated financial market, in modern economies reflects their economic development level. The stock market indicates the mood of investors in the development of a country and is an important ingredient for growth. Objectives: This paper aims to introduce an additional statistical tool used to support the decision-making process in stock trading, and it investigate the usage of statistical process control (SPC) methods into the stock trading process. Methods/Approach: The individual (I), exponentially weighted moving average (EWMA) and cumulative s
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Naderi, M. H., Asghar Seif, and M. Bameni Moghadam. "Integration of Multivariate Loss Function Approach in the Hotelling’s Charts under Banerjee-Rahim (1988) Weibull Shock Models." Austrian Journal of Statistics 50, no. 3 (2021): 13–31. http://dx.doi.org/10.17713/ajs.v50i3.857.

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A proper monitoring of stochastic systems is the control charts of statistical process control and drift in characteristics of output may be due to one or several assignable causes. Although many research works have been done on the economic design of control charts with single assignable cause, the economic statistical design of T^2 control chart under Weibull shock model with multiple assignable causes and considering multivariate Taguchi loss function has not been presented yet. Using Taguchi loss function in the concept of quality control charts with economic and economic statistical desig
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Caballero-Morales, Santiago-Omar. "Building Cost Function 3D Benchmarks to Improve the Economic Statistical Design ofX¯Control Charts." Mathematical Problems in Engineering 2014 (2014): 1–20. http://dx.doi.org/10.1155/2014/879456.

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Shewhart or control charts are important Statistical Process Control (SPC) techniques used for prompt detection of failures in a manufacturing process and minimization of production costs which are modelled with nonlinear functions (cost functions). Heuristic methods have been used to find the chart’s parameters integrated within the cost function that best comply with economic and statistical restrictions. However heuristic estimation is highly dependent on the size of the search space, the set of initial solutions, and the exploration operators. In this paper the 3D analysis of the cost func
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Torng, James C. C., Jeffery K. Cochran, Douglas C. Montgomery, and Frederick P. Lawrence. "Implementing Statistically Constrained Economic EWMA Control Charts." Journal of Quality Technology 27, no. 3 (1995): 257–64. http://dx.doi.org/10.1080/00224065.1995.11979598.

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Dissertations / Theses on the topic "Economic statistical control charts"

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Grayson, James M. (James Morris). "Economic Statistical Design of Inverse Gaussian Distribution Control Charts." Thesis, University of North Texas, 1990. https://digital.library.unt.edu/ark:/67531/metadc332397/.

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Statistical quality control (SQC) is one technique companies are using in the development of a Total Quality Management (TQM) culture. Shewhart control charts, a widely used SQC tool, rely on an underlying normal distribution of the data. Often data are skewed. The inverse Gaussian distribution is a probability distribution that is wellsuited to handling skewed data. This analysis develops models and a set of tools usable by practitioners for the constrained economic statistical design of control charts for inverse Gaussian distribution process centrality and process dispersion. The use of thi
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Ghebretensae, Manna Zerai. "A unified approach to the economic aspects of statistical quality control and improvement." Thesis, Stellenbosch : Stellenbosch University, 2004. http://hdl.handle.net/10019.1/49865.

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Assignment (MSc)--Stellenbosch University, 2004.<br>ENGLISH ABSTRACT: The design of control charts refers to the selection of the parameters implied, including the sample size n, control limit width parameter k, and the sampling interval h. The design of the X -control chart that is based on economic as well as statistical considerations is presently one of the more popular subjects of research. Two assumptions are considered in the development and use of the economic or economic statistical models. These assumptions are potentially critical. It is assumed that the time between process s
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Noronha, Rossano Santos. "Projeto Econômico da Carta de Controle X : um modelo com custos dependentes dos desvios." Universidade do Vale do Rio dos Sinos, 2017. http://www.repositorio.jesuita.org.br/handle/UNISINOS/6276.

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Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2017-05-22T13:46:14Z No. of bitstreams: 1 Rossano Santos Noronha_.pdf: 585085 bytes, checksum: 88117b318c3e9c30134fce5bf0bdc22e (MD5)<br>Made available in DSpace on 2017-05-22T13:46:14Z (GMT). No. of bitstreams: 1 Rossano Santos Noronha_.pdf: 585085 bytes, checksum: 88117b318c3e9c30134fce5bf0bdc22e (MD5) Previous issue date: 2017-03-07<br>CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>Devido à dificuldade em se estimar os custos de operação associados ao monitoramento estatístico do processo nos trabalhos iden
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Thoutou, Sayi Mbani. "Quality control charts under random fuzzy measurements." Master's thesis, University of Cape Town, 2007. http://hdl.handle.net/11427/19140.

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Includes bibliographical references. .<br>We consider statistical process control charts as tools that statistical process control utilizes for monitoring changes; identifying process variations and their causes in industrial processes (manufacturing processes) and which help manufacturers to take the appropriate action, rectify problems or improve manufacturing processes so as to produce good quality products. As an essential tool, researchers have always paid attention to the development of process control charts. Also, the sample sizes required for establishing control charts are often unde
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Yang, Hualong, and 阳华龙. "Statistical process control charts with known and estimatedparameters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50900018.

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Monitoring and detection of abrupt changes for multivariate processes are becoming increasingly important in modern manufacturing environments. Typical equipment may have multiple key variables to be measured continuously. Hotelling's 〖T 〗^2and CUSUM charts were widely applied to solve the problem of monitoring the mean vector of multivariate quality measurements. Besides, a new multivariate cumulative sum chart (MCUSUM) is introduced where the target shift mean is assumed to be a weighted sum of principal directions of the population covariance matrix. In practical problems, estimated parame
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Wilson, Sara R. "Control Charts with Missing Observations." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/37623.

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Traditional control charts for process monitoring are based on taking samples from the process at regular time intervals. However, it is often possible in practice for observations, and even entire samples, to be missing. This dissertation investigates missing observations in Exponentially Weighted Moving Average (EWMA) and Multivariate EWMA (MEWMA) control charts. The standardized sample mean is used since this adjusts the sample mean for the fact that part of the sample may be missing. It also allows for constant control limits even though the sample size varies randomly. When complete sampl
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el, homani Abdellatif. "NOVEL APPROACHES FOR STATISTICAL PROCESS CONTROL CHARTS PATTERN RECOGNITION." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/dissertations/152.

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Fast and accurate recognition of the Statistical Control Chart Patterns (SPCCP) is significant for supervising manufacturing processes to accomplish better control and to make high value products. SPCCP can display eight kinds of patterns: normal, stratification, systematic, increasing trend, decreasing trend, up shift, down shift and cyclic. With the exception of the natural pattern, all other patterns indicate that the supervised manufacturing process is not performing properly and actions need to be taken to correct the problems. This research proposes new approaches, neural networks and ne
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Sargut, Kamil Umut. "Application Of Statistical Process Control To Software Development Processes Via Control Charts." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1270081/index.pdf.

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The application of Statistical Process Control (SPC) to software processes has been a challenging issue for software engineers and researchers. Although SPC is suggested for providing process control and achieving higher process maturity levels, there are very few resources that describe success stories, implementation details, and implemented guidelines for applying SPC to specific metrics. In this thesis the findings of a case study that is performed for investigating the applicability of SPC to software metrics in an emergent CMM Level 3 software organization are presented. As being one of
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Love, Nicole S. (Nicole Sharlene). "Statistical process control charts for the computer-aided fabrication environment." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35437.

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Ronnestrand, Clinton. "Using control charts to determine if a process is in statistical process control." Online version, 2009. http://www.uwstout.edu/lib/thesis/2009/2009ronnestrandc.pdf.

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Books on the topic "Economic statistical control charts"

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N, Goh T., and Kuralmani V, eds. Statistical models and control charts for high-quality processes. Kluwer Academic Publishers, 2002.

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Wise, Stephen A. Innovative control charting: Practical SPC solutions for today's manufacturing environment. ASQ Quality Press, 1998.

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Collani, Elart Von. The economic design of control charts. B.G. Teubner, 1989.

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von Collani, Elart. The Economic Design of Control Charts. Vieweg+Teubner Verlag, 1989. http://dx.doi.org/10.1007/978-3-322-94763-5.

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Xie, M., T. N. Goh, and V. Kuralmani. Statistical Models and Control Charts for High-Quality Processes. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1015-4.

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Papaioannou, D. Statistical quality control in the construction industry: Theory and implementation of control charts. UMIST, 1997.

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Advanced topics in statistical process control: The power of Shewhart's charts. SPC Press, 1995.

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Statistical quality control in high reliability systems. Garland Pub., 1994.

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Meijer, Rob R. The use of statistical process control-charts for person-fit analysis in computerized adaptive testing. Law School Admission Council, 2003.

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Tagaras, George. A dynamic programming approach to the economic design of X-charts. INSEAD, 1992.

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Book chapters on the topic "Economic statistical control charts"

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Woodall, W. H. "Conflicts Between Deming’s Philosophy and the Economic Design of Control Charts." In Frontiers in Statistical Quality Control. Physica-Verlag HD, 1987. http://dx.doi.org/10.1007/978-3-662-11787-3_16.

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Xie, M., T. N. Goh, and V. Kuralmani. "Economic Design of Geometric Chart." In Statistical Models and Control Charts for High-Quality Processes. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1015-4_9.

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Saniga, E. M. "Heuristic Economical Designs for X̅ and R Control Charts." In Frontiers in Statistical Quality Control. Physica-Verlag HD, 1987. http://dx.doi.org/10.1007/978-3-662-11787-3_14.

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Celano, G., and S. Fichera. "Statistical Economic Design of an X Control Chart." In AMST ’99. Springer Vienna, 1999. http://dx.doi.org/10.1007/978-3-7091-2508-3_100.

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Saniga, Erwin, James Lucas, Darwin Davis, and Thomas McWilliams. "Economic Control Chart Policies for Monitoring Variables When There Are Two Components of Variance." In Frontiers in Statistical Quality Control 10. Physica-Verlag HD, 2012. http://dx.doi.org/10.1007/978-3-7908-2846-7_6.

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Lam, K. K., and M. A. Rahim. "Joint Determination of Economic Design of % MathType!MTEF!2!1!+- % feaagaart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn % hiov2DGi1BTfMBaeXatLxBI9gBamXvP5wqonvsaeHbd9wDYLwzYbqe % e0evGueE0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9fr % Fj0-OqFfea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYx % e9vr0-vr0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaeHbfv % 3ySLgzaGqbciqb-Hfayzaaraaaaa!3AD9! $$ \bar X $$ -Control Charts, Economic Production Quantity, and Production Run Length for a Deteriorating Production System." In Frontiers in Statistical Quality Control 7. Physica-Verlag HD, 2004. http://dx.doi.org/10.1007/978-3-7908-2674-6_5.

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Ohta, Hiroshi, and Etsuko Kusukawa. "An Application of Confirmation Sample Control Chart in the High-Yield Processes and Its Economic Design." In Frontiers in Statistical Quality Control 7. Physica-Verlag HD, 2004. http://dx.doi.org/10.1007/978-3-7908-2674-6_7.

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Luceño, Alberto. "Control Charts." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_187.

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Hubbard, Merton R. "Control Charts." In Statistical Quality Control for the Food Industry. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4684-0041-0_3.

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Hubbard, Merton R. "Control Charts." In Statistical Quality Control for the Food Industry. Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-1197-4_3.

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Conference papers on the topic "Economic statistical control charts"

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Fong-Jung, Yu,. "An Economic-Statistical Design of X-Bar Control Charts Using Taguchi Loss Functions." In Information Control Problems in Manufacturing, edited by Bakhtadze, Natalia, chair Dolgui, Alexandre and Bakhtadze, Natalia. Elsevier, 2009. http://dx.doi.org/10.3182/20090603-3-ru-2001.00287.

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García-Díaz, J. Carlos, M. Martínez-Gómez, and Vicente Jesus Segui. "Economic-Statistical Design of Effective Variance Control Charts, ∕Sp∕[sup 1∕p]." In THIRD MANUFACTURING ENGINEERING SOCIETY INTERNATIONAL CONFERENCE: MESIC-09. AIP, 2009. http://dx.doi.org/10.1063/1.3273645.

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Chen, Fei Long, and Li Lun Yeh. "Economic statistical design of x-bar control charts for correlated data and Gamma failure mechanism with genetic algorithm." In Industrial Engineering (CIE-40). IEEE, 2010. http://dx.doi.org/10.1109/iccie.2010.5668330.

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Caballero-Morales, Santiago-Omar, and Abdur Rahim. "Analyzing the effect of non-normality on the solution space for the economic statistical design of X-bar control charts." In 2015 International Conference on Industrial Engineering and Operations Management (IEOM). IEEE, 2015. http://dx.doi.org/10.1109/ieom.2015.7093766.

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Al-Buenain, Ahmad Abdulla, Damla Kizilay, Ozge Buyukdagli, and M. Fatih Tasgetiren. "A Novel Differential Evolution Algorithm with Q-Learning for Economical and Statistical Design of X-Bar Control Charts." In 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2020. http://dx.doi.org/10.1109/cec48606.2020.9185625.

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Yeong, Wai Chung, Michael Boon Chong Khoo, Sok Li Lim, and Wei Lin Teoh. "Effects of misspecification of the loss function on the economic-statistical design of the synthetic X̄ chart." In 2015 International Conference on Computer, Communications, and Control Technology (I4CT). IEEE, 2015. http://dx.doi.org/10.1109/i4ct.2015.7219541.

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Lesina, Mario, and Lovorka Gotal Dmitrovic. "APPLICATION OF SPC AND GROWTH MODELS ON THE ECONOMIC TRAJECTORY OF THE LEATHER AND FOOTWEAR INDUSTRY." In NORDSCI International Conference. SAIMA Consult Ltd, 2020. http://dx.doi.org/10.32008/nordsci2020/b2/v3/01.

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The paper shows the relation among the number of small, medium and large companies in the leather and footwear industry in Croatia, as well as the relation among the number of their employees by means of the Spearman and Pearson correlation coefficient. The data were collected during 21 years. The warning zone and the risk zone were determined by means of the Statistical Process Control (SPC) for a certain number of small, medium and large companies in the leather and footwear industry in Croatia. Growth models, based on externalities, models based on research and development and the AK models
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Mohammadian, F., and K. Paynabar. "Economic design of acceptance control charts." In 2008 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2008. http://dx.doi.org/10.1109/ieem.2008.4738248.

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Abdella Zidan Amhemad. "Effect of non normality on statistical control charts." In 2010 International Conference on Networking and Information Technology (ICNIT 2010). IEEE, 2010. http://dx.doi.org/10.1109/icnit.2010.5508459.

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Lu, Shin-Li, Chen-Fang Tsai, and Jen Hsiang Chen. "EWMA Control Charts for Statistical Detecting QoS Violations." In 2015 IEEE 12th International Conference on e-Business Engineering (ICEBE). IEEE, 2015. http://dx.doi.org/10.1109/icebe.2015.41.

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Reports on the topic "Economic statistical control charts"

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National report 2009-2019 - Rural NEET in Turkey. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nrtr.2020.12.

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This report describes the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Turkey. To achieve this goal, the report portrays indicators of youth population, youth employment and unemployment, education and NEETs distribution. Since the urban/rural distinction is not clear in Turkey, the overtime change in the status of the Rural NEETs can-not be analysed.The adopted statistical procedures across the different selected dimensions involves descriptive longitudinal analysis, using graphical d
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National report 2009-2019 - Rural NEET in Montenegro. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nrme.2020.12.

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This report outlines in detail the situation of rural Youths Neither in Employment, nor in Edu-cation or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Montenegro. To do this, the report utilised indicators of: youth population; youth employment and unemployment; education; and, NEETs distribution. The characterisation of all indicators adopted the degree of urbanisation as a central criterion, enabling propor-tional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age subgroups and,
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National report 2009-2019 - Rural NEET in Spain. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nres.2020.12.

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This report outlines in detail the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Spain. To do this, the report utilised indicators of: youth population; youth employment and unemployment; education; and, NEETs distribution. The characterisation of all indicators adopted the degree of urbanisation as a central criterion, enabling propor-tional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age subgroups and, where
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National report 2009-2019 - Rural NEET in Portugal. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nrpt.2020.12.

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This report outlines in detail the situation of rural youths Neither in Employment, nor in Edu-cation or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Portugal. To do this, the report portrays indicators of: youth population; youth em-ployment and unemployment; education; and, NEETs distribution. The characterisation of all indicators adopts the degree of urbanisation as a central criterion, thereby enabling propor-tional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age subgroup
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National report 2009-2019 - Rural NEET in Croatia. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nrhr.2020.12.

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This report presents the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) in Croatia, aged between 15 and 34 years old, in the period from 2009 until 2019. To achieve this goal, the report utilised indicators of youth population, youth em-ployment and unemployment, education and NEETs distribution. The characterisation of all indicators adopted the degree of urbanisation as a central criteria, enabling comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further collapsed into age sub-groups and, when possible,
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National report 2009-2019 - Rural NEET in Bulgaria. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.ndbg.2020.12.

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This report outlines in detail the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Bulgaria. To do this, the report utilised indicators of: youth population; you-th employment and unemployment; education; and, NEETs distribution. The characteri-sation of all indicators adopted the degree of urbanisation as a central criterion, enabling proportional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age subgroups and, w
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National reports 2009-2019 - Rural NEET across Europe (14 countries reports). OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nr14.2020.12.

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This report outlines in detail the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Bosnia and Herzegovina. To do this, the report utilised indicators of: you-th population; youth employment and unemployment; education; and, NEETs distribution. The characterisation of all indicators adopted the degree of urbanisation as a central cri-terion, enabling proportional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age su
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National report 2009-2019 - Rural NEET in Germany. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nrde.2020.12.

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This report outlines in detail the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Germany. To do this, the report utilised indicators of: youth population; youth employment and unemployment; education; and, NEETs distribution. The characte-risation of all indicators adopted the degree of urbanisation as a central criterion, enabling proportional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age subgroups and, whe
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National report 2009-2019 - Rural NEET in Bosnia-Herzegovina. OST Action CA 18213: Rural NEET Youth Network: Modeling the risks underlying rural NEETs social exclusion, 2020. http://dx.doi.org/10.15847/cisrnyn.nrba.2020.12.

Full text
Abstract:
This report outlines in detail the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Bosnia and Herzegovina. To do this, the report utilised indicators of: you-th population; youth employment and unemployment; education; and, NEETs distribution. The characterisation of all indicators adopted the degree of urbanisation as a central cri-terion, enabling proportional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age su
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