Course detail
Numerical and Statistical Treatment of Experimental Data
FCH-BCA_ZDSAcad. year: 2012/2013
The course extends the knowledge gained in the previous study. Based on statistical physico-chemical and biological disciplines taught in the study of Consumer chemistry. It focuses on data processing, use of normal distribution, hypothesis testing and analysis of sources of error and measurement uncertainty.
It also deals with planning and management of experiments in chemistry, biology and physics. The data processing is used especially MS Excel, statistical software, and software for image and signal analysis.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Learning outcomes of the course unit
- Comprehensive information on the basic numerical methods for data processing, basic methods of numerical processing simple dependencies and data smoothing.
- Practical application of acquired knowledge in the processing of experimental data from selected topics in MS-Excel and Origin.
- Theoretical and practical knowledge and skills in measurement uncertainty.
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
Assesment methods and criteria linked to learning outcomes
Course curriculum
1. Statistical surveys - data collection
2. Data processing, display and analysis of basic data
3. Expressing variability
4. Mean of grouped data, weighted average
5. Measures of position
6. Correlation
7. Linear regression
Part II - Normal distribution (Week V - VIII)
8. Binomial distribution
9. Normal distribution
10. Distribution of average
11. Distribution of parts
12. Confidence intervals
Part III - Testovní hypotheses (Week IX - X)
13. Testing of hypotheses I and II
Part IV - Uncertainty of measurement (week of XI - XII)
14. Uncertainty direct measurements
15. Uncertainty of indirect measurements
16. Combined and expanded uncertainty
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Meloun M., Militký J. : Kompendium statistického zpracování dat. Academia, Praha 2002 (CS)
Šťastný Z. : Matematické a statistické výpočtu v Microsoft® Excelu. Computer Press, Brno 1999 (CS)
Recommended reading
Carley A. F., Morgan P. H. : Computaional Methods in the Chemical Sciences. Ellis Horwood Limited, Chichester 1989 (CS)
Graham R.C. : Data Analysis for the Chemical Sciences. VCH Publishers, Inc., New York 1993 (CS)
Green J. R., Margerison D. : Statistical treatment of experimental data. Elsevier Sci. Publ. Comp., Amsterodam 1978 (CS)
Schnoor J.L. : Environmental Modeling. John Wiley a Sons, Inc., New York 1996 (CS)
Classification of course in study plans
- Programme BPCP_CHCHT Bachelor's
branch BPCO_SCH , 3 year of study, winter semester, compulsory
- Programme BKCP_CHCHT Bachelor's
branch BKCO_SCH , 3 year of study, winter semester, compulsory
- Programme BPCP_CHCHT_AKR Bachelor's
branch BPCO_SCH , 3 year of study, winter semester, compulsory
- Programme CKCP_CZV lifelong learning
branch CKCO_CZV , 1 year of study, winter semester, compulsory