Statistical Methods with elements of computer modeling

The graduates of natural sciences and life sciences area

compulsory course

Number of lecture hours- 12 h

Number of laboratory classes hours- 4 h

W01: One can select adequate statistical method for the specification of data and propose a solution to the research problem W02: One knows the basic parameters of validation and able to plan laboratory tests to determine them

U01: One can perform calculations based on data obtained from measurements of instrumental methods including the statistical analysis, prepares reports

U02: One knows and is able to define the rules of accreditation and certification of laboratories; understands the problems of the functioning of the quality system; uses the knowledge of the standards for laboratories

K01: One is able to organize work in the group and maximize the efficiency of its operations

- lectures as a multimedia presentations;

- one by one and on-line consultations (distance learning);

- laboratory exercises instructions prepared based on the information giving during the lectures are useful and required at the laboratory;

- individual work with the apparatus and advanced analytical equipment under the teacher supervision;

In addition, for all students are prepared printed materials and laboratory instructions.

Introduction to the chemometric methods in environmental chemistry: statistical tests, data classification, planning experiments, linear and nonlinear regression. Learning the basics of modeling in environmental chemistry. Validation of analytical methods.

Lectures:

The measurement theory. Parametric and nonparametric statistical tests. Design of experiment. Data classification methods. Artificial neural networks. The theory of computer modeling - transport of pollutants in water and soil. Three-dimensional modeling by using GIS systems.

Laboratory classes:

Using shared and specialized software to solve practical environmental problems relating to subject issues.

Examination:

Lecture: Assessment based on exam

Lab activities: Pass unrated based on lab activities, frequency and active participation in classes.

Lecture:

The aim of the course is to acquaint students with basic issues of statistics, which can be used to analyze chemical data. The lecture is divided into several subtopics. At the beginning the basic statistics and statistical tests are presented. Another issue is related to the classification of multidimensional data, which are an introduction to the modeling data. Also are discussed: linear and nonlinear regression, artificial neural networks and GIS modeling as well as the general overview of modeling of pollutants in environmental matrices transportation. The last issue is validation of analytical methods.

Laboratory classes:

The laboratory activities are planned for series of exercises in the computer lab and the analytical labs as well. In particular, will be presented the advanced applications of Excel, Statistica, Curve Expert, and GIS software.

1. J. Mazerski. Podstawy chemometrii, Wydawnictwo PG, Gdańsk, 2000;

2. D. Zuba (red.) - Chemometria: metody i zastosowania, Wyd. IES, Kraków, 2003

3. R.G. Brereton, Chemometrics, John Wiley & Sons, Chichester, 2003;

4. J.N. Miller, Statistics and chemometrics for analytical chemistry, Prentice Hali, Harlow, 2000;

5. M. Otto, Chemometrics, Wiley-VCH, Weinheim, 1999;

6. Einax, J.W., Zwanziger, H.W., Geiss, S., 1997. Chemometrics in Environmental Analysis. Wiley, Weinheim.

7. E. Bulska, Metrologia Chemiczna, Wyd. Malamut, Warszawa 2008.

Wiley, Weinheim.

Student - graduate student:

1. identifies and distinguish between issues related to the classes topic;

2. are able to find and use the required literature in English and Polish;

3. are using, applying and explaining the subject terminology related

to the study issues (not using laboratory slang) in English

and its counterparts in Polish;

4. are applying in practice the theoretical knowledge how to operate

by the apparatus and small laboratory equipment in a correct and proper way as well. Making self measurements based on the knowledge he/she gained;

5. preparing their own preparations for analysis, creating analytical procedures and standard procedures;

6. independently examines, interprets and calculates the results obtained

in the laboratory. Applying the appropriate analytical procedures. Preparing writing research reports and notes, which may be the useful for issuing the scientific publications;

7. compares, explains and describes obtained results in comparison with the available standards and literature. Predicting behavior and probable scenarios in the laboratory during sample preparation as well as the same study (e.g. principles of health and safety in the workplace).

The pass mark class is attendance at lectures and active participation, knowledge of analytical procedures is required for proper implementation of the exercise-laboratory analysis.

Course assessment is based on the frequency and participation in the classes as well as receiving a positive evaluation at an oral, final exam.

not provided