The aim of studying and bibliography

The main aim of study: Knowledge of statistical methods for evaluation of the experiment results.

The general information about the module: The student gains knowledge about the basic methods of statistical analysis of the results of experimental studies, as well as he becomes familiar with the STATISTICA system.

Teaching materials: Materiały dydaktyczne opublikowane na stronach Zakładu Informatyki Chemicznej

Bibliography required to complete the module

Bibliography used during lectures

1

B. Dębska, B.Guzowska-Świder

Statystyka i opracowanie wyników

Oficyna wydawnicza Politechniki Rzeszowskiej.

2011

Bibliography used during classes/laboratories/others

1	B. Dębska, B.Guzowska-Świder	Statystyka i opracowanie wyników	Oficyna wydawnicza Politechniki Rzeszowskiej.	2011
2	StatSoft	Manual System STATISTICA for Windows	Wyd. Stat Soft Polska Sp. z.o.o., Kraków .	2012

Bibliography to self-study

1	J. Czermiński, A. Iwasiewicz, Z. Paszek, A. Sikorski	Metody statystyczne w doświadczalnictwie chemicznym	WNT, Warszawa.	1984
2	A. Stanisz	Przystępny kurs statystyki w oparciu o program STATISTICA PL	Wyd. Stat Soft Polska Sp. z. o.o., Kraków .	1999
3	B. Dębska, B. Guzowska-Świder	kurs Statystyka	www.e-chemia.pl.	2011

Basic requirements in category knowledge/skills/social competences

Formal requirements: Credit required mathematics, information technology

Basic requirements in category knowledge: Basic knowledge of probability

Basic requirements in category skills: Ability to use a computer.

Basic requirements in category social competences: Ability to work individually and in a group

Module outcomes

MEK	The student who completed the module	Types of classes / teaching methods leading to achieving a given outcome of teaching	Methods of verifying every mentioned outcome of teaching	Relationships with KEK	Relationships with OEK
01	has the ability to use statistical methods to describe the chemical processes.	Interactive lecture, laboratory, e-learning	Final test	K_W001+++	T1A_W01+ T1A_W04++
02	has a basic ability to use programs that are designed to elaborate results of analytical experimentals	laboratory, e-learning	observation of the task performance	K_W008+++	T1A_W02+ T1A_W04++
03	can use basic practical methods, techniques, tools and materials used in solving the basic engineering tasks associated with chemical technology	laboratory	observation of the task performance	K_W015+	T1A_W04++ T1A_W07++
04	has the ability to use knowledge of mathematical statistics to pose and test hypotheses in the field of chemistry experiments and interpret their results	interactive lecture	test	K_U013+++	T1A_U09++
05	has the ability to use computational methods to solve problems from the scope of chemical technology	interactive lecture, laboratory	observation of the task performance	K_U010++	T1A_U08++
06	has an acquired habit of systematic self-education and improving its professional knowledge through the knowledge updating.	interactive lecture, laboratory at which the student solves the problems	observation of the task performance	K_U006+++	T1A_U05+

Attention: Depending on the epidemic situation, verification of the achieved learning outcomes specified in the study program, in particular credits and examinations at the end of specific classes, can be implemented remotely (real-time meetings).

The syllabus of the module

Sem.	TK	The content	realized in	MEK
3	TK01	LIMS (Laboratory Information Management System) – selected problems.	W01	MEK01 MEK06
3	TK02	Experimental database. Rejection outliers in data. Selective use of data	W02	MEK03 MEK06
3	TK03	Exploratory data analysis of the analytical measurements, descriptive statistics, cross-sectional data, normality tests, statistical graphs. The frequency distribution of a variable	W03	MEK02
3	TK04	Statistical hypothesis testing. Parametric and non-parametric tests.	W04	MEK04
3	TK05	Multiple regression. Study of correlation between variables	W05	MEK05
3	TK06	One-way and multiple analysis of variance. Discriminant analysis, factor analysis and principal components analysis.	W06	MEK03
3	TK07	Fitting the observed variable distribution to a theoretical distribution.	W07	MEK02
3	TK08	Management of Statistica program data. Parameters of variable distribution.	L01	MEK02 MEK06
3	TK09	Study of empirical variable distribution. Statistical inference- nonparametric tests.	L02	MEK03
3	TK10	Statistical inference - parametric tests.	L03	MEK04
3	TK11	Analysis of the relationship between variables: linear and non-linear regression.	L04	MEK05
3	TK12	Analysis of Variance.	L05	MEK03

The student's effort

The type of classes	The work before classes	The participation in classes	The work after classes
Lecture (sem. 3)		contact hours: 15.00 hours/sem.	complementing/reading through notes: 4.00 hours/sem. Studying the recommended bibliography: 7.00 hours/sem.
Laboratory (sem. 3)	The preparation for a Laboratory: 5.00 hours/sem. The preparation for a test: 5.00 hours/sem.	contact hours: 15.00 hours/sem.	Finishing/Making the report: 5.00 hours/sem.
Advice (sem. 3)
Credit (sem. 3)	The preparation for a Credit: 3.00 hours/sem.	Others: 1.00 hours/sem.

The way of giving the component module grades and the final grade

The type of classes	The way of giving the final grade
Lecture	Lecture: credit course based on the evaluation of the test – OW
Laboratory	Computer laboratory: credit based on the evaluation of completed tasks – OL
The final grade	Final evaluation of the module is calculated by the following formula: OK = 50% OW + 50% OL

Sample problems

Required during the exam/when receiving the credit
(-)

Realized during classes/laboratories/projects
(-)

Others
(-)

Can a student use any teaching aids during the exam/when receiving the credit : no

The contents of the module are associated with the research profile: no