ECTS
ECTS Course Catalogue
Course details
Course code: ZJS10090o16Semester: 2016/2017 summer
Name: Statistics
Major: Food Quality Management and Analysis
Study Type: first cycle
Course type: compulsory
Study Semester: 2
ECTS points: 4
Hours (Lectures / Tutorials / Other): 30 / 30 / 0
Lecturer: dr hab. Andrzej Michalski
Language of instruction: Polish
Learning outcomes: Knowledge: The student knows the theoretical basics and he has the practical abilities in the field of exploratory data analysis of the constructing statistical models and the studying of a structure and a dynamics of random phenomena. He knows the basic problems of mathematical statistics: point and interval estimation, hypothesis testing; the probability distributions and statistical methods used in quality management and food analysis. Skills: The student can apply the learned principles of exploratory data analysis to their transparent presentation, he can perform correctly statistical inference, select and apply appropriate statistical model to describe the studied phenomenon based on empirical data, select and apply appropriate statistical methods for quality control and food analysis, prepare a report containing the results statistical analysis using the statistical package (e.g. STATISTICA, EXCEL (unit-Data Analysis).
Competences: Student is aware of the possibility of applying different models and statistical methods to solve problems of varying degrees of advancement in the field of quality management and food analysis. He understands the randomness of phenomena, nature and the need for practical application of a statistical model and can perform correctly statistical inference, and the results he can use practically.
Prerequisites: mathematics, informatics
Course content: Basic concepts of descriptive statistics: population, random sample, typology of characteristics of the population. Basic statistics (numerical characteristics) and the graphical presentation of empirical material. Basic concepts of probability: the probability of a random variable, density function, types and examples of probability distributions (such as used in quality management and food analysis). Point estimation, confidence intervals, confidence level, statistical hypothesis, a critical set of a test and significance level. Verification of hypotheses and basic statistical parametric and nonparametric tests, methods of regression analysis. Selected methods of qualitative data analysis.
Recommended literature: 1. Teaching materials elaborated by lecturer Koronacki J., Mielniczuk J. (2001). Statystyka dla studentów kierunków technicznych i przyrodniczych. WNT, Warszawa. Sobczyk M. (1998). Statystyka. Podstawy teoretyczne, przykłady – zadania. Wydawnictwo UMCS - Lublin. Dąbrowski A., Gnot S., Michalski A., Srzednicka J. (1997). Statystyka - 15 godzin z pakietem Statgraphics. Wyd. AR - Wrocław, Wyd. 3. Krysicki W., Bartos J., Dyczka W., Królikowska K., Wasilewski M. (1998). Rachunek prawdopodobieństwa i statystyka matematyczna w zadaniach. Część I. Statystyka matematyczna. Część II. PWN, Warszawa, , Wyd. XXIV. Abramowicz, H. (1992). Jak analizować wyniki pomiarów? Wyd. PWN, Warszawa.
Assessment methods: Credit of classes according to: tests (to 15 min.), solution of problems from given lists of tasks (at table and using a computer), activity (additional points), accomplished report on the base of selected experimental data, home-tasks and final repetition - at least 60% requested points.
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