Code - Б3.Б10
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Type of course unit - compulsory |
Level of course unit - second cycle |
Year of study -3 |
Semester - 5 |
Number of ECTS credits allocated - 2 |
Name of lecturer – Ms Vlada Kovalenko
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Learning outcomes of the course unit – After this course the student should be able to: Understand and explain the concept of statistical quality control; Indentify, formulate and solve problem of poor quality products by statistical methods and tools; Use computer for statistical data manipulation (such software as Excel, Statistica, etc.) |
Mode of delivery - face-to-face, distance learning
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Prerequisites and co-requisites – preliminary and applicable requirements of Federal National Educational Standard |
Recommended optional program components – business game, cases |
Course contents: Distributions of quality indicators by quantitative and qualitative attributes; Analysis of the accuracy of the process; The main tools of statistical control; Characteristics of the various plans for inspection by attributes; Testing the hypothesis of a distribution function; Quality improvement tools
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Recommended or required reading. Required reading: 1) Carlberg, Conrad Statistical analysis: Microsoft Excel 2010, 1st ed. – Que, 2011. – 464 p. 2) Montgomery, Douglas C. Introduction to Statistical Quality Control, 6th edition. – NY: John Wiley & Sons, 2009. – 741 p. 3) Zimmerman, Steven M. Statistical quality control using Excel, 2nd edition / Steven M. Zimmerman, Marjorie L. Icenogle. – Milwaukee, Wisconsin: ASQ Quality Press, 2003. – 447 p. Recommended reading: 1) Hastie, Travor The elements of statistical learning: data mining, inference and prediction, 2nd ed. (Springer series in Statistics) / Trevor Hastie, Robert Tibshirani, Jerome Friedman. – Springer, 2009. – 768 p. 2) Izenman, Alan J. Modern multivariate statistical techniques: regression, classification and manifold learning (Springer texts in Statistics), 1st ed. – Springer, 2008. – 760 p. 3) Ott, R. Lyman An introduction to statistical methods and data analysis / R. Lyman Ott, Micheal T. Lonqnecker, 6th ed. – Duxbury Press, 2008. – 1273 p. 4) Bishop, Christopher M. Pattern recognition and machine learning (information science and statistics), 1st ed. – Springer, 2006. – 738 p. 5) Kachiqan Sam Kash Statistical analysis: an interdisciplinary introduction to univariate & multivariate methods. – Radius Press, 1986. – 589 p. 6) Komarov, V.I. Application of statistical methods of control and quality management of technological processes, products and monitoring and services: tutorial / V.I. Komarov, T.M Vladimirova, V.I. Zhabin, V.V. Zalyazhnyh, A.E. Koptelov, S.I. Tretyakov. - Arkhangelsk: ASTU, 2009. – 174 p. 7) Zalyazhnyh, V.V. Statistical methods of control and quality management: tutorial / V.V. Zalyazhnyh, A.E. Koptelov. – Arkhangelsk: ASTU, 2004. – 88 p. |
Planned learning activities: laboratory works, workshops, presentations, tests And teaching methods: work both in groups and without assistance.
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Assessment methods: laboratory practice - U/G#, assignment and exam – U (poor), C (satisfactory), B (good), A (excellent) and criteria: attendance, completeness of tasks fulfillment, sufficiency of theoretical explanation of them
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Language of instruction |
Work placement(s) – computer class |