ZUT - Krajowe Ramy Kwalifikacji / Rok 0001/0001 / Wydział Ekonomiczny / Economics 28.09.2023 transfer (S1) / Property Valuation and Real Estate Transactions / Sylabus przedmiotu

Wydział Ekonomiczny - Economics 28.09.2023 transfer (S1)
specjalność: Property Valuation and Real Estate Transactions

Sylabus przedmiotu Econometry:

Informacje podstawowe

Kierunek studiów	Economics 28.09.2023 transfer
Forma studiów	studia stacjonarne	Poziom	pierwszego stopnia
Tytuł zawodowy absolwenta	licencjat
Obszary studiów	charakterystyki PRK
Profil	ogólnoakademicki
Moduł	—
Przedmiot	Econometry
Specjalność	przedmiot wspólny
Jednostka prowadząca	Katedra Zastosowań Matematyki w Ekonomii
Nauczyciel odpowiedzialny	Maciej Oesterreich <Maciej.Oesterreich@zut.edu.pl>
Inni nauczyciele	Iwona Bąk <Iwona.Bak@zut.edu.pl>, Katarzyna Cheba <Katarzyna.Cheba@zut.edu.pl>, Joanna Perzyńska <joanna.perzynska@zut.edu.pl>
ECTS (planowane)	4,0	ECTS (formy)	4,0
Forma zaliczenia	egzamin	Język	polski
Blok obieralny	—	Grupa obieralna	—

Formy dydaktyczne

Forma dydaktyczna	KOD	Semestr	Godziny	ECTS	Waga	Zaliczenie
wykłady	W	3	20	1,6	0,50	egzamin
laboratoria	L	3	30	2,4	0,50	zaliczenie

Wymagania wstępne

KOD	Wymaganie wstępne
W-1	Basic knowledge of mathematics, descriptive statistics as well as general economic knowledge.
W-2	Skill to use the Excel spreadsheet.

Cele przedmiotu

KOD	Cel modułu/przedmiotu
C-1	To develop skills in the construction and assessment of linear and non-linear econometric models.
C-2	Gaining practical skills in the application of econometric methods in practice with the application of Excel spreadsheet.
C-3	Acquiring the knowledge about construction and solving mathematical decision models and interpretation of the obtained results.
C-4	Obtaining basic knowledge of the applications of econometric methods in the study of regularities in phenomena occurring in the economy.

Treści programowe z podziałem na formy zajęć

KOD	Treść programowa	Godziny
laboratoria
T-L-1	Construction of an econometric model. Classification of variables in a model, classification of econometric models. Construction of a model hypothesis based on the description of the relationship between the variables.	2
T-L-2	Selection of independent variables for the econometric model - the Hellwig's method.	2
T-L-3	Test concerning construction of an econometric model, variable classification, model classification, Hellwig's method.	1
T-L-4	Estimation and validation of a single-equation econometric model with two (or more) independent variables (linear, power form). Application of Excel and Statistica.	5
T-L-5	Estimation and validation of trend models (linear, exponential form) and time series models with constant and relatively constant seasonality. Application of Excel and Statistica.	5
T-L-6	Test concerning the estimation and validation of econometric models with two (or more) independent variables and time series models.	2
T-L-7	Construction of decision models.	2
T-L-8	Solving linear programming problems with the geometric method.	3
T-L-9	Solving linear programming problems using the SIMPLEX method - traditionally and with the application of Excel (Solver add-in).	6
T-L-10	Test concerning methods of solving linear programming problems.	2
		30
wykłady
T-W-1	Areas of applications of mathematics in economics. Relations of econometrics with other sciences disciplines.	1
T-W-2	The econometric model and its structure. Classification of variables in the model, classification of models, stages of the econometric modeling process.	3
T-W-3	Determination of structural coefficients of a single-equation econometric model with multiple independent variables using the least squares method. Model quality assessment (measures of goodness of fit, examination of the significance of coefficients of the model, examination of the autocorrelation of the random component).	4
T-W-4	Econometric modeling of time series - trend models (linear, exponential), time series models with seasonal fluctuations.	4
T-W-5	The decision model and its structure. Decision model vs. the econometric model. Examples of linear programs – construction a decision model for example programs.	3
T-W-6	Methods of solving linear programming problems - the geometrical method and the SIMPLEX method.	4
T-W-7	Using an Excel spreadsheet (Solver add-in) to solve linear programming problems using the simplex method.	1
		20

Obciążenie pracą studenta - formy aktywności

KOD	Forma aktywności	Godziny
laboratoria
A-L-1	The participation in classes	30
A-L-2	The preparation to classes.	8
A-L-3	The literature study of the subject.	8
A-L-4	The preparation to the tests.	8
A-L-5	Homeworks.	6
		60
wykłady
A-W-1	The participation in classes.	20
A-W-2	The literature study of the subject.	8
A-W-3	Preparation for the exam.	10
A-W-4	Exam	2
		40

Metody nauczania / narzędzia dydaktyczne

KOD	Metoda nauczania / narzędzie dydaktyczne
M-1	The information and problem lecture with the use of a multimedia presentation.
M-2	Laboratory exercises with the use of a computer along with a didactic discussion related to the lecture.

Sposoby oceny

KOD	Sposób oceny
S-1	Ocena podsumowująca: Written exam concerning lectures, containing theoretical issues and tasks to be solved on one's own.
S-2	Ocena formująca: Tests to evaluate periodic student achievements.
S-3	Ocena formująca: Evaluation the results of homework done independently and in a team aimed at identifying gaps in the knowledge and skills of the student.
S-4	Ocena podsumowująca: Passing laboratory exercises on the basis of grades from tests, homework and activity during classes.

Zamierzone efekty kształcenia - wiedza

Zamierzone efekty kształcenia	Odniesienie do efektów kształcenia dla kierunku studiów	Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	Cel przedmiotu	Treści programowe	Metody nauczania	Sposób oceny
Ec_1A_B08_W01 The student knows the role and place of econometrics in economic analysis and research and knows the stages of the econometric modeling process.	Ec_1A_W01, Ec_1A_W07, Ec_1A_W06	—	C-4, C-3	T-W-1, T-L-1, T-L-2, T-W-2, T-L-3, T-L-6	M-1, M-2	S-1, S-4, S-3, S-2
Ec_1A_B08_W02 The student knows popular statistical software packages and knows how to use econometric knowledge to solve tasks on socio-economic issues	Ec_1A_W01, Ec_1A_W07, Ec_1A_W06	—	C-1, C-2	T-L-4, T-L-5, T-W-7, T-L-9, T-L-6	M-2, M-1	S-2, S-3
Ec_1A_B08_W03 The student has knowledge about constructing and solving mathematical decision models.	Ec_1A_W01, Ec_1A_W03, Ec_1A_W07, Ec_1A_W06	—	C-3	T-L-8, T-L-9, T-W-7, T-L-7, T-W-6, T-W-5, T-L-10	M-1, M-2	S-1, S-2

Zamierzone efekty kształcenia - umiejętności

Zamierzone efekty kształcenia	Odniesienie do efektów kształcenia dla kierunku studiów	Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	Cel przedmiotu	Treści programowe	Metody nauczania	Sposób oceny
Ec_1A_B08_U01 Student is able to apply appropriate econometric methods and tools and make interpretation of the results of conducted research, as well as refer them to business practice.	Ec_1A_U01, Ec_1A_U02, Ec_1A_U03, Ec_1A_U11, Ec_1A_U12	—	C-1, C-2	T-L-1, T-L-2, T-L-4, T-L-5, T-W-3	M-1, M-2	S-1, S-2
Ec_1A_B08_U02 Student is able to build, solve and make interpretion of mathematical decision models.	Ec_1A_U01, Ec_1A_U02, Ec_1A_U03, Ec_1A_U07, Ec_1A_U08, Ec_1A_U09, Ec_1A_U12, Ec_1A_U21	—	C-3	T-W-6, T-L-8, T-W-5, T-L-9	M-1, M-2	S-1, S-2

Zamierzone efekty kształcenia - inne kompetencje społeczne i personalne

Zamierzone efekty kształcenia	Odniesienie do efektów kształcenia dla kierunku studiów	Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	Cel przedmiotu	Treści programowe	Metody nauczania	Sposób oceny
Ec_1A_B08_K01 The student has mastered the principles of self-solving problems	Ec_1A_K01, Ec_1A_K04	—	C-1, C-2	T-L-4, T-L-5, T-L-8, T-L-9	M-2	S-3, S-2

Kryterium oceny - wiedza

Efekt kształcenia	Ocena	Kryterium oceny
Ec_1A_B08_W01 The student knows the role and place of econometrics in economic analysis and research and knows the stages of the econometric modeling process.	2,0	The student does not know the role and place of econometrics in economic analysis and research, he does not know the stages of econometric modeling.
	3,0	Student poorly knows the role and place of econometrics in economic analysis and research, knows only some stages of econometric modeling.
	3,5	Student poorly knows the role and place of econometrics in economic analysis and research, knows most of the stages of econometric modeling.
	4,0	The student knows the role and place of econometrics in economic analysis and research, knows only some stages of econometric modeling.
	4,5	The student knows the role and place of econometrics in economic analysis and research, knows the stages of econometric modeling.
	5,0	The student knows the role and place of econometrics in economic analysis and research, knows the stages of econometric modeling and can analyze them.
Ec_1A_B08_W02 The student knows popular statistical software packages and knows how to use econometric knowledge to solve tasks on socio-economic issues	2,0	The student does not know the statistical packages and does not know how to use his knowledge to solve tasks on socio-economic issues.
	3,0	The student correctly knows several modules of statistical packages and knows (with the help of the teacher) how to use econometric knowledge to solve tasks on socio-economic issues.
	3,5	The student knows all the modules of the known statistical packages and knows (with the help of the teacher) how to use econometric knowledge to solve (indicated by the teacher) tasks on socio-economic issues.
	4,0	The student knows all the modules of the known statistical packages and knows how to use econometric knowledge to solve (indicated by the teacher) tasks on socio-economic issues.
	4,5	The student knows all modules of the known statistical packages and knows how to use your econometric knowledge to solve independently proposed tasks on socio-economic issues
	5,0	The student can independently propose the use of appropriate econometric tools, is able to assess their suitability to the study of socio-economic phenomena, knows how to use all modules of the known statistical packages
Ec_1A_B08_W03 The student has knowledge about constructing and solving mathematical decision models.	2,0	Student nie ma wiedzy na temat budowy i rozwiązywania modeli decyzji matematycznych.
	3,0	The student has knowledge about the construction of some decision models but does not know how to solve them.
	3,5	The student has knowledge about the construction of decision models and knows the graphic method.
	4,0	The student has knowledge about the construction of decision models and knows methods and how to solve them (graphic method and simplex algorithm).
	4,5	The student has knowledge about the construction of decision models, knows methods and their solutions (graphic method and simplex algorithm) and make interpretation with help of the teacher.
	5,0	The student has knowledge about the construction of decision models, knows methods and their solutions and interpretations.

Kryterium oceny - umiejętności

Efekt kształcenia	Ocena	Kryterium oceny
Ec_1A_B08_U01 Student is able to apply appropriate econometric methods and tools and make interpretation of the results of conducted research, as well as refer them to business practice.	2,0	The student is not able to use statistical packages in the econometric modeling.
	3,0	The student is able to use, presented during classes, statistical packages in the econometric modeling only with the help of the teacher.
	3,5	The student is able to use some statistical packages in econometric modeling.
	4,0	Student uses statistical packages the in econometric modeling.
	4,5	Student uses statistical packages the in econometric modeling. It can make interpretation of the obtained results with help of the teacher.
	5,0	Student uses independently statistical packages in econometric modeling. Is able to independently make interpretation of the obtained results and make their presentation.
Ec_1A_B08_U02 Student is able to build, solve and make interpretion of mathematical decision models.	2,0	The student is not able to construct decision models.
	3,0	Student is able to construct decision models.
	3,5	Student is able to construct decision models and solves them using the graphical method.
	4,0	Student is able to construct decision models and solves them using the simplex method and the graphical algorithm.
	4,5	Student is able to construct decision models and solves them using the simplex method and the graphical algorithm. Is able to make interpretation of their results with help of the teacher.
	5,0	Student is able to construct decision models and solves them using the simplex method and the graphical algorithm. Is able to independently make interpretation of their results.

Kryterium oceny - inne kompetencje społeczne i personalne

Efekt kształcenia	Ocena	Kryterium oceny
Ec_1A_B08_K01 The student has mastered the principles of self-solving problems	2,0	The student has not mastered the principles of self-solving research problems.
	3,0	The student is able to independently conduct an econometric study, and with the teacher's help organize a group presentation.
	3,5	The student is able to conduct an individual econometric study and organize a group presentation.
	4,0	The student has mastered the principles of individual and team work, can independently organize and conduct an individual or group presentation, with the teacher's help is able to identify the methods and tools needed to solve the defined problem and make a preliminary analysis of the results.
	4,5	The student has mastered the principles of individual and team work, can independently organize and conduct an individual or group presentation, is able to identify methods and tools needed to solve a defined problem, and make a comprehensive analysis of the results.
	5,0	The student has mastered the principles of individual and team work, can independently organize and conduct an individual or group presentation, is able to identify methods and tools needed to solve a defined problem, is able to make a comprehensive analysis of the results obtained and use all modules of known statistical packages.

Literatura podstawowa

Maddala G.S., Introduction to Econometrics, Wiley, New York, 2011, 4
Anderson D.R., Sweeney D.J., Williams T.A., Statistics for Business and Economics, South-Western Cengage Learning, Manson, 2019, 14
Aczel A.D., Souderpandian J., Complete Business Statistics, McGraw-Hill/Irwin, 2008, 7
Hiller F.S., Lieberman G.J., Introduction to operations research, McGraw-Hill, 2021, 11
Bąk I., Markowicz I., Mojsiewicz M., Wawrzyniak K., Formulas and Tables, CeDeWu, Warszawa, 2021, 1

Literatura dodatkowa

Hozer J. (red.), Ekonometria, Uniwersytet Szczeciński, Szczecin, 1997
Hozer J. (red.), Ekonometria stosowana w przykładach i zadaniach, Katedra Ekonometrii i Statystyki Uniwersytetu Szczecińskiego, Stowarzyszenie Pomoc i Rozwój, Szczecin, 2007
Goryl A., Jędrzejczyk Z., Kukuła K., Wprowadzenie do ekonometrii, PWN, Warszawa, 2009
Jędrzejczyk Z., Kukuła K., Skrzypek J., Badania operacyjne w przykładach i zadaniach, PWN, Warszawa, 2015
Szapiro T. (red.), Decyzje menadżerskie z Excelem, PWE, Warszawa, 2000
Bąk I., Markowicz I., Mojsiewicz M., Wawrzyniak K., Wzory i tablice. Metody statystyczne i ekonometryczne, CeDeWu, Warszawa, 2019, 2
Hozer J. (red.), Mikroekonometria. Analizy. Diagnozy. Prognozy, PWE, Warszawa, 1993
Jajuga K., Ekonometria. Metody i analizy problemów ekonomicznych, Wyd. Akademii Ekonomicznej im. O. Langego we Wrocławiu, Wrocław, 1999

Treści programowe - laboratoria

KOD	Treść programowa	Godziny
T-L-1	Construction of an econometric model. Classification of variables in a model, classification of econometric models. Construction of a model hypothesis based on the description of the relationship between the variables.	2
T-L-2	Selection of independent variables for the econometric model - the Hellwig's method.	2
T-L-3	Test concerning construction of an econometric model, variable classification, model classification, Hellwig's method.	1
T-L-4	Estimation and validation of a single-equation econometric model with two (or more) independent variables (linear, power form). Application of Excel and Statistica.	5
T-L-5	Estimation and validation of trend models (linear, exponential form) and time series models with constant and relatively constant seasonality. Application of Excel and Statistica.	5
T-L-6	Test concerning the estimation and validation of econometric models with two (or more) independent variables and time series models.	2
T-L-7	Construction of decision models.	2
T-L-8	Solving linear programming problems with the geometric method.	3
T-L-9	Solving linear programming problems using the SIMPLEX method - traditionally and with the application of Excel (Solver add-in).	6
T-L-10	Test concerning methods of solving linear programming problems.	2
		30

Treści programowe - wykłady

KOD	Treść programowa	Godziny
T-W-1	Areas of applications of mathematics in economics. Relations of econometrics with other sciences disciplines.	1
T-W-2	The econometric model and its structure. Classification of variables in the model, classification of models, stages of the econometric modeling process.	3
T-W-3	Determination of structural coefficients of a single-equation econometric model with multiple independent variables using the least squares method. Model quality assessment (measures of goodness of fit, examination of the significance of coefficients of the model, examination of the autocorrelation of the random component).	4
T-W-4	Econometric modeling of time series - trend models (linear, exponential), time series models with seasonal fluctuations.	4
T-W-5	The decision model and its structure. Decision model vs. the econometric model. Examples of linear programs – construction a decision model for example programs.	3
T-W-6	Methods of solving linear programming problems - the geometrical method and the SIMPLEX method.	4
T-W-7	Using an Excel spreadsheet (Solver add-in) to solve linear programming problems using the simplex method.	1
		20

Formy aktywności - laboratoria

KOD	Forma aktywności	Godziny
A-L-1	The participation in classes	30
A-L-2	The preparation to classes.	8
A-L-3	The literature study of the subject.	8
A-L-4	The preparation to the tests.	8
A-L-5	Homeworks.	6
		60

(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

Formy aktywności - wykłady

KOD	Forma aktywności	Godziny
A-W-1	The participation in classes.	20
A-W-2	The literature study of the subject.	8
A-W-3	Preparation for the exam.	10
A-W-4	Exam	2
		40

(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	Ec_1A_B08_W01	The student knows the role and place of econometrics in economic analysis and research and knows the stages of the econometric modeling process.
Odniesienie do efektów kształcenia dla kierunku studiów	Ec_1A_W01	He / she knows and understands at an advanced level the issues in the field of economics and finance, their place in the social sciences system and connections with other scientific disciplines
	Ec_1A_W07	He / she knows and understands at an advanced level the issues in the field of quantitative methods (including mathematics, statistics, econometrics and decision-making theory) and examples of their applications in economic practice
	Ec_1A_W06	He / she knows and understands at an advanced level the methods and tools (including IT) of obtaining, processing and presenting data on socio-economic phenomena and processes
Cel przedmiotu	C-4	Obtaining basic knowledge of the applications of econometric methods in the study of regularities in phenomena occurring in the economy.
Cel przedmiotu	C-3	Acquiring the knowledge about construction and solving mathematical decision models and interpretation of the obtained results.
Treści programowe	T-W-1	Areas of applications of mathematics in economics. Relations of econometrics with other sciences disciplines.
	T-L-1	Construction of an econometric model. Classification of variables in a model, classification of econometric models. Construction of a model hypothesis based on the description of the relationship between the variables.
	T-L-2	Selection of independent variables for the econometric model - the Hellwig's method.
	T-W-2	The econometric model and its structure. Classification of variables in the model, classification of models, stages of the econometric modeling process.
	T-L-3	Test concerning construction of an econometric model, variable classification, model classification, Hellwig's method.
	T-L-6	Test concerning the estimation and validation of econometric models with two (or more) independent variables and time series models.
Metody nauczania	M-1	The information and problem lecture with the use of a multimedia presentation.
Metody nauczania	M-2	Laboratory exercises with the use of a computer along with a didactic discussion related to the lecture.
Sposób oceny	S-1	Ocena podsumowująca: Written exam concerning lectures, containing theoretical issues and tasks to be solved on one's own.
	S-4	Ocena podsumowująca: Passing laboratory exercises on the basis of grades from tests, homework and activity during classes.
	S-3	Ocena formująca: Evaluation the results of homework done independently and in a team aimed at identifying gaps in the knowledge and skills of the student.
	S-2	Ocena formująca: Tests to evaluate periodic student achievements.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student does not know the role and place of econometrics in economic analysis and research, he does not know the stages of econometric modeling.
	3,0	Student poorly knows the role and place of econometrics in economic analysis and research, knows only some stages of econometric modeling.
	3,5	Student poorly knows the role and place of econometrics in economic analysis and research, knows most of the stages of econometric modeling.
	4,0	The student knows the role and place of econometrics in economic analysis and research, knows only some stages of econometric modeling.
	4,5	The student knows the role and place of econometrics in economic analysis and research, knows the stages of econometric modeling.
	5,0	The student knows the role and place of econometrics in economic analysis and research, knows the stages of econometric modeling and can analyze them.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	Ec_1A_B08_W02	The student knows popular statistical software packages and knows how to use econometric knowledge to solve tasks on socio-economic issues
Odniesienie do efektów kształcenia dla kierunku studiów	Ec_1A_W01	He / she knows and understands at an advanced level the issues in the field of economics and finance, their place in the social sciences system and connections with other scientific disciplines
	Ec_1A_W07	He / she knows and understands at an advanced level the issues in the field of quantitative methods (including mathematics, statistics, econometrics and decision-making theory) and examples of their applications in economic practice
	Ec_1A_W06	He / she knows and understands at an advanced level the methods and tools (including IT) of obtaining, processing and presenting data on socio-economic phenomena and processes
Cel przedmiotu	C-1	To develop skills in the construction and assessment of linear and non-linear econometric models.
Cel przedmiotu	C-2	Gaining practical skills in the application of econometric methods in practice with the application of Excel spreadsheet.
Treści programowe	T-L-4	Estimation and validation of a single-equation econometric model with two (or more) independent variables (linear, power form). Application of Excel and Statistica.
	T-L-5	Estimation and validation of trend models (linear, exponential form) and time series models with constant and relatively constant seasonality. Application of Excel and Statistica.
	T-W-7	Using an Excel spreadsheet (Solver add-in) to solve linear programming problems using the simplex method.
	T-L-9	Solving linear programming problems using the SIMPLEX method - traditionally and with the application of Excel (Solver add-in).
	T-L-6	Test concerning the estimation and validation of econometric models with two (or more) independent variables and time series models.
Metody nauczania	M-2	Laboratory exercises with the use of a computer along with a didactic discussion related to the lecture.
Metody nauczania	M-1	The information and problem lecture with the use of a multimedia presentation.
Sposób oceny	S-2	Ocena formująca: Tests to evaluate periodic student achievements.
Sposób oceny	S-3	Ocena formująca: Evaluation the results of homework done independently and in a team aimed at identifying gaps in the knowledge and skills of the student.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student does not know the statistical packages and does not know how to use his knowledge to solve tasks on socio-economic issues.
	3,0	The student correctly knows several modules of statistical packages and knows (with the help of the teacher) how to use econometric knowledge to solve tasks on socio-economic issues.
	3,5	The student knows all the modules of the known statistical packages and knows (with the help of the teacher) how to use econometric knowledge to solve (indicated by the teacher) tasks on socio-economic issues.
	4,0	The student knows all the modules of the known statistical packages and knows how to use econometric knowledge to solve (indicated by the teacher) tasks on socio-economic issues.
	4,5	The student knows all modules of the known statistical packages and knows how to use your econometric knowledge to solve independently proposed tasks on socio-economic issues
	5,0	The student can independently propose the use of appropriate econometric tools, is able to assess their suitability to the study of socio-economic phenomena, knows how to use all modules of the known statistical packages

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	Ec_1A_B08_W03	The student has knowledge about constructing and solving mathematical decision models.
Odniesienie do efektów kształcenia dla kierunku studiów	Ec_1A_W01	He / she knows and understands at an advanced level the issues in the field of economics and finance, their place in the social sciences system and connections with other scientific disciplines
	Ec_1A_W03	He / she knows and understands at an advanced level the relations between social institutions and their structures on a national and international scale
	Ec_1A_W07	He / she knows and understands at an advanced level the issues in the field of quantitative methods (including mathematics, statistics, econometrics and decision-making theory) and examples of their applications in economic practice
	Ec_1A_W06	He / she knows and understands at an advanced level the methods and tools (including IT) of obtaining, processing and presenting data on socio-economic phenomena and processes
Cel przedmiotu	C-3	Acquiring the knowledge about construction and solving mathematical decision models and interpretation of the obtained results.
Treści programowe	T-L-8	Solving linear programming problems with the geometric method.
	T-L-9	Solving linear programming problems using the SIMPLEX method - traditionally and with the application of Excel (Solver add-in).
	T-W-7	Using an Excel spreadsheet (Solver add-in) to solve linear programming problems using the simplex method.
	T-L-7	Construction of decision models.
	T-W-6	Methods of solving linear programming problems - the geometrical method and the SIMPLEX method.
	T-W-5	The decision model and its structure. Decision model vs. the econometric model. Examples of linear programs – construction a decision model for example programs.
	T-L-10	Test concerning methods of solving linear programming problems.
Metody nauczania	M-1	The information and problem lecture with the use of a multimedia presentation.
Metody nauczania	M-2	Laboratory exercises with the use of a computer along with a didactic discussion related to the lecture.
Sposób oceny	S-1	Ocena podsumowująca: Written exam concerning lectures, containing theoretical issues and tasks to be solved on one's own.
Sposób oceny	S-2	Ocena formująca: Tests to evaluate periodic student achievements.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	Student nie ma wiedzy na temat budowy i rozwiązywania modeli decyzji matematycznych.
	3,0	The student has knowledge about the construction of some decision models but does not know how to solve them.
	3,5	The student has knowledge about the construction of decision models and knows the graphic method.
	4,0	The student has knowledge about the construction of decision models and knows methods and how to solve them (graphic method and simplex algorithm).
	4,5	The student has knowledge about the construction of decision models, knows methods and their solutions (graphic method and simplex algorithm) and make interpretation with help of the teacher.
	5,0	The student has knowledge about the construction of decision models, knows methods and their solutions and interpretations.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	Ec_1A_B08_U01	Student is able to apply appropriate econometric methods and tools and make interpretation of the results of conducted research, as well as refer them to business practice.
Odniesienie do efektów kształcenia dla kierunku studiów	Ec_1A_U01	He / she can use the possessed scientific knowledge to interpret socio-economic phenomena
	Ec_1A_U02	He / she can apply the possessed theoretical knowledge, properly selecting data, methods and tools, to formulate and solve unusual and complex problems related to socio-economic processes and phenomena, and to solve tasks in conditions that are not fully predictable
	Ec_1A_U03	He / she can plan and organise individual work and cooperate with other people as part of team activities
	Ec_1A_U11	He / she can analyse the indicated solutions to specific problems and propose appropriate solutions in this regard
	Ec_1A_U12	He / she can analyse social phenomena
Cel przedmiotu	C-1	To develop skills in the construction and assessment of linear and non-linear econometric models.
Cel przedmiotu	C-2	Gaining practical skills in the application of econometric methods in practice with the application of Excel spreadsheet.
Treści programowe	T-L-1	Construction of an econometric model. Classification of variables in a model, classification of econometric models. Construction of a model hypothesis based on the description of the relationship between the variables.
	T-L-2	Selection of independent variables for the econometric model - the Hellwig's method.
	T-L-4	Estimation and validation of a single-equation econometric model with two (or more) independent variables (linear, power form). Application of Excel and Statistica.
	T-L-5	Estimation and validation of trend models (linear, exponential form) and time series models with constant and relatively constant seasonality. Application of Excel and Statistica.
	T-W-3	Determination of structural coefficients of a single-equation econometric model with multiple independent variables using the least squares method. Model quality assessment (measures of goodness of fit, examination of the significance of coefficients of the model, examination of the autocorrelation of the random component).
Metody nauczania	M-1	The information and problem lecture with the use of a multimedia presentation.
Metody nauczania	M-2	Laboratory exercises with the use of a computer along with a didactic discussion related to the lecture.
Sposób oceny	S-1	Ocena podsumowująca: Written exam concerning lectures, containing theoretical issues and tasks to be solved on one's own.
Sposób oceny	S-2	Ocena formująca: Tests to evaluate periodic student achievements.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student is not able to use statistical packages in the econometric modeling.
	3,0	The student is able to use, presented during classes, statistical packages in the econometric modeling only with the help of the teacher.
	3,5	The student is able to use some statistical packages in econometric modeling.
	4,0	Student uses statistical packages the in econometric modeling.
	4,5	Student uses statistical packages the in econometric modeling. It can make interpretation of the obtained results with help of the teacher.
	5,0	Student uses independently statistical packages in econometric modeling. Is able to independently make interpretation of the obtained results and make their presentation.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	Ec_1A_B08_U02	Student is able to build, solve and make interpretion of mathematical decision models.
Odniesienie do efektów kształcenia dla kierunku studiów	Ec_1A_U01	He / she can use the possessed scientific knowledge to interpret socio-economic phenomena
	Ec_1A_U02	He / she can apply the possessed theoretical knowledge, properly selecting data, methods and tools, to formulate and solve unusual and complex problems related to socio-economic processes and phenomena, and to solve tasks in conditions that are not fully predictable
	Ec_1A_U03	He / she can plan and organise individual work and cooperate with other people as part of team activities
	Ec_1A_U07	He / she is able to solve macro- and microeconomic problems with the use of various analytical tools, including modern information technologies
	Ec_1A_U08	He / she can properly analyse the causes and the course of social processes and phenomena in the field of economics and finance
	Ec_1A_U09	He / she can forecast social processes and phenomena with the use of standard research methods
	Ec_1A_U12	He / she can analyse social phenomena
	Ec_1A_U21	He / she is able to continue learning throughout his / her life
Cel przedmiotu	C-3	Acquiring the knowledge about construction and solving mathematical decision models and interpretation of the obtained results.
Treści programowe	T-W-6	Methods of solving linear programming problems - the geometrical method and the SIMPLEX method.
	T-L-8	Solving linear programming problems with the geometric method.
	T-W-5	The decision model and its structure. Decision model vs. the econometric model. Examples of linear programs – construction a decision model for example programs.
	T-L-9	Solving linear programming problems using the SIMPLEX method - traditionally and with the application of Excel (Solver add-in).
Metody nauczania	M-1	The information and problem lecture with the use of a multimedia presentation.
Metody nauczania	M-2	Laboratory exercises with the use of a computer along with a didactic discussion related to the lecture.
Sposób oceny	S-1	Ocena podsumowująca: Written exam concerning lectures, containing theoretical issues and tasks to be solved on one's own.
Sposób oceny	S-2	Ocena formująca: Tests to evaluate periodic student achievements.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student is not able to construct decision models.
	3,0	Student is able to construct decision models.
	3,5	Student is able to construct decision models and solves them using the graphical method.
	4,0	Student is able to construct decision models and solves them using the simplex method and the graphical algorithm.
	4,5	Student is able to construct decision models and solves them using the simplex method and the graphical algorithm. Is able to make interpretation of their results with help of the teacher.
	5,0	Student is able to construct decision models and solves them using the simplex method and the graphical algorithm. Is able to independently make interpretation of their results.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	Ec_1A_B08_K01	The student has mastered the principles of self-solving problems
Odniesienie do efektów kształcenia dla kierunku studiów	Ec_1A_K01	He / she is ready to define priorities for the implementation of tasks set by himself / herself or others
Odniesienie do efektów kształcenia dla kierunku studiów	Ec_1A_K04	He / she is willing to think and act in an entrepreneurial manner
Cel przedmiotu	C-1	To develop skills in the construction and assessment of linear and non-linear econometric models.
Cel przedmiotu	C-2	Gaining practical skills in the application of econometric methods in practice with the application of Excel spreadsheet.
Treści programowe	T-L-4	Estimation and validation of a single-equation econometric model with two (or more) independent variables (linear, power form). Application of Excel and Statistica.
	T-L-5	Estimation and validation of trend models (linear, exponential form) and time series models with constant and relatively constant seasonality. Application of Excel and Statistica.
	T-L-8	Solving linear programming problems with the geometric method.
	T-L-9	Solving linear programming problems using the SIMPLEX method - traditionally and with the application of Excel (Solver add-in).
Metody nauczania	M-2	Laboratory exercises with the use of a computer along with a didactic discussion related to the lecture.
Sposób oceny	S-3	Ocena formująca: Evaluation the results of homework done independently and in a team aimed at identifying gaps in the knowledge and skills of the student.
Sposób oceny	S-2	Ocena formująca: Tests to evaluate periodic student achievements.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student has not mastered the principles of self-solving research problems.
	3,0	The student is able to independently conduct an econometric study, and with the teacher's help organize a group presentation.
	3,5	The student is able to conduct an individual econometric study and organize a group presentation.
	4,0	The student has mastered the principles of individual and team work, can independently organize and conduct an individual or group presentation, with the teacher's help is able to identify the methods and tools needed to solve the defined problem and make a preliminary analysis of the results.
	4,5	The student has mastered the principles of individual and team work, can independently organize and conduct an individual or group presentation, is able to identify methods and tools needed to solve a defined problem, and make a comprehensive analysis of the results.
	5,0	The student has mastered the principles of individual and team work, can independently organize and conduct an individual or group presentation, is able to identify methods and tools needed to solve a defined problem, is able to make a comprehensive analysis of the results obtained and use all modules of known statistical packages.