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 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	Metody statystyczne dla chemików	PWN, Warszawa.	1992
2		STATISTICA w badaniach naukowych i nauczaniu statystyki	Wyd. Stat Soft Polska Sp. z. o.o., Kraków .	2010
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, computer sciences

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 PRK
01	has the ability to use statistical methods to describe the chemical processes.	interactive lecture, laboratory	test
02	has a basic ability to use programs that are useful in engineering activities	laboratory	observation of the task performance
03	can use basic practical methods, techniques, tools and materials used in solving the basic tasks associated with pharmaceutical engineering.	laboratory	observation of the task performance
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
05	has the ability to use computational methods to solve problems from the scope of pharmaceutical engineering.	interactive lecture, laboratory	observation of the task performance
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

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 on the basis of the test – OW
Laboratory	Computer laboratory: credit on the basis 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: yes

1	A. Czerniecka-Kubicka; L. Dobrowolski; K. Hęclik; I. Zarzyka	Kompozyt polimerowy oraz sposób wytwarzania kompozytu polimerowego	2024
2	K. Butt; M. Garczyńska; E. Hajduk; M. Jaromin; J. Kostecka; A. Mazur-Pączka; G. Pączka	Effects of Energy Crop Monocultures and Sewage Sludge Fertiliser on Soils and Earthworm Community Attributes	2023
3	L. Dobrowolski; K. Hęclik; M. Jaromin; I. Zarzyka	A Practical Test of Distance Learning During the COVID-19 Lockdown	2023
4	M. Bakar; A. Białkowska; A. Czerniecka-Kubicka; L. Dobrowolski; K. Hęclik; B. Krzykowska; M. Longosz; I. Zarzyka	Polymer Biocompositions and Nanobiocomposites Based on P3HB with Polyurethane and Montmorillonite	2023
5	M. Chmiela; A. Czerniecka-Kubicka; L. Dobrowolski; W. Gonciarz; K. Hęclik; M. Longosz; A. Szyszkowska; D. Trzybiński; K. Woźniak; A. Wróbel; I. Zarzyka	Molecular Modeling of 3-chloro-3-phenylquinoline-2,4-dione, Crystal Structure and Cytotoxic Activity for developments in a potential new drug	2023
6	M. Bakar; A. Białkowska; A. Czerniecka-Kubicka; L. Dobrowolski; K. Hęclik; B. Krzykowska; I. Zarzyka	Biobased poly(3-hydroxybutyrate acid) composites with addition of aliphatic polyurethane based on polypropylene glycols	2022
7	J. Buczkowicz; T. Drzazga; G. Fic; M. Jaromin; P. Krajewski; P. Matysik; R. Mazur; P. Milczarski; T. Sikora; M. Szeliga; D. Tyrka; M. Tyrka; E. Witkowski	Selekcja genomowa pszenicy ozimej	2021
8	K. Buut; M. Garczyńska; M. Jaromin; J. Kostecka; A. Mazur-Pączka; G. Pączka; A. Podolak	Community structure of Lumbricidae in beech woodland of the Bieszczady National Park, Southeast Poland	2021
9	M. Bakar; A. Białkowska; A. Czerniecka-Kubicka; L. Dobrowolski; K. Hęclik; K. Leś; M. Pyda; M. Walczak; I. Zarzyka	Thermally stable biopolymer composites based on poly(3-hydroxybutyrate) modified with linear aliphatic polyurethanes – preparation and properties	2021
10	A. Białkowska; L. Dobrowolski; L. Wianowski; I. Zarzyka	Physical blowing agents for polyurethanes	2020
11	A. Bocian; J. Buczkowicz; K. Hus; M. Jaromin; J. Legath; D. Łysiak; V. Petrilla; M. Petrillova; S. Sławek	Comparison of Methods for Measuring Protein Concentration in Venom Samples	2020
12	A. Czerniecka-Kubicka; L. Dobrowolski; K. Hęclik; I. Zarzyka	Biodegradowalne kompozyty polimerowe na osnowie P3HB	2020
13	M. Jaromin; Ł. Opaliński	Wybrane metody prognozowania tempa rozwoju dyscyplin naukowych (indeks citing half-life, metoda regresji nieliniowej, linearyzowanej i wielomianowej drugiego stopnia)	2020
14	M. Jaromin; Ł. Opaliński	Wybrane metody prognozowania tempa rozwoju dyscyplin naukowych (metoda regresji wielomianowej trzeciego stopnia, metoda autoregresji oraz wygładzania wykładniczego)	2020
15	R. Bartosik; L. Dobrowolski; K. Hęclik; A. Klasek; A. Lycka; I. Zarzyka	New mono- and diesters with imidazoquinolinone ring- synthesis, structure characterization and molecular modeling	2020
16	A. Bocian; J. Buczkowicz; K. Hus; M. Jaromin; J. Legath	An effective method of isolating honey proteins	2019
17	B. Dębska; L. Dobrowolski; M. Inger; M. Jaromin; M. Wilk	Komputerowo-wspomagane obliczanie bilansu masowego i cieplnego instalacji chemicznej	2019