ZUT - Krajowe Ramy Kwalifikacji / Rok 2012/2013 / Wydział Ekonomiczny / Zarządzanie (N1) / Przedsiębiorstwo w gospodarce opartej na wiedzy / Sylabus przedmiotu

Wydział Ekonomiczny - Zarządzanie (N1)
specjalność: Przedsiębiorstwo w gospodarce opartej na wiedzy

Sylabus przedmiotu Statistics:

Informacje podstawowe

Kierunek studiów	Zarządzanie
Forma studiów	studia niestacjonarne	Poziom	pierwszego stopnia
Tytuł zawodowy absolwenta	licencjat
Obszary studiów	nauk społecznych
Profil	ogólnoakademicki
Moduł	—
Przedmiot	Statistics
Specjalność	przedmiot wspólny
Jednostka prowadząca	Katedra Zastosowań Matematyki w Ekonomii
Nauczyciel odpowiedzialny	Aneta Becker <aneta.becker@zut.edu.pl>
Inni nauczyciele
ECTS (planowane)	5,0	ECTS (formy)	5,0
Forma zaliczenia	zaliczenie	Język	angielski
Blok obieralny	12	Grupa obieralna	14

Formy dydaktyczne

Forma dydaktyczna	KOD	Semestr	Godziny	ECTS	Waga	Zaliczenie
wykłady	W	4	30	5,0	1,00	zaliczenie

Wymagania wstępne

KOD	Wymaganie wstępne
W-1	Basic, academic level of knowledge in mathematics, basics of information technology, as well as general knowledge of economics.

Cele przedmiotu

KOD	Cel modułu/przedmiotu
C-1	The objective of the course is to provide students with knowledge on the basic descriptive methods and inferential statistics. The acquired knowledge should serve as a basis for further advanced courses.
C-2	During the course the students get familiar with basic methods of descriptive statistics and statistical inference. These methods are intended to provide tools for decision making under uncertainty, using sample data.
C-3	The course contains an overview of graphical and numerical methods for summarizing data as well as basic notions of inferential statistics, including basic distributions, estimation theory, confidence intervals, statistical hypothesis testing, simple linear regression, and index numbers.

Treści programowe z podziałem na formy zajęć

KOD	Treść programowa	Godziny
wykłady
T-W-1	Introduction to statistics. Basic notions. Data sources. Different Types of Data. Examples of applications of statistics.	4
T-W-2	Summary descriptive measures. Descriptive methods and exploratory data analysis. Graphical presentation of data. Numerical measures of center, dispersion and asymmetry.	5
T-W-3	Basic notions of probability theory. Random variable and its distribution.	4
T-W-4	Estimation of population parameters. Estimator and its properties. Standard error of estimation. Confidence intervals.	4
T-W-5	Testing statistical hypothesis. Parametric significance tests. Chi-square test. One-way ANOVA F test.	4
T-W-6	Regression and correlation analysis. Two-dimensional distributions. Contingency tables and chi-square test for independence. Significance tests for Spearman’s and Pearson’s correlation coefficients. Simple linear regression model. Testing the signi-ficance of the structural parameters.	5
T-W-7	Index numbers. Average growth rate.	4
		30

Obciążenie pracą studenta - formy aktywności

KOD	Forma aktywności	Godziny
wykłady
A-W-1	Participation in lectures	30
A-W-2	Participation in the consultation	30
A-W-3	The study of literature	20
A-W-4	Develop formulas	10
A-W-5	Implementation of housework	28
A-W-6	Preparing for the Exam	30
A-W-7	Participation in the exam	2
		150

Metody nauczania / narzędzia dydaktyczne

KOD	Metoda nauczania / narzędzie dydaktyczne
M-1	Informational lecture - illustrated with slides and examples of a practical nature in a chosen utility environment, discussion about solutions from literature and practice.
M-2	Classes based on solving problems and practical standard exercises.
M-3	Students use handbooks, statistical tables and statistical software.

Sposoby oceny

KOD	Sposób oceny
S-1	Ocena podsumowująca: The final exam has a written form and consists of two parts: standard exercises and a test.

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
ZN1_1A_OJ7_W01 The student knows the basic concepts and methods of analysis used in statistics and selected methods of statistical inference.	ZN1_1A_W01, ZN1_1A_W06, ZN1_1A_W07	S1A_W01, S1A_W05, S1A_W06	C-1, C-2, C-3	T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6, T-W-7	M-1, M-2, M-3	S-1
ZN1_1A_OJ7_W02 The student knows the popular statistical packages, and knows how to leverage their statistical knowledge to solve problems of socio-economic issues.	ZN1_1A_W06	S1A_W05	C-1, C-2, C-3	T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6, T-W-7	M-2, M-3	S-1

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
ZN1_1A_OJ7_U01 Students can formulate the problem using statistical concepts, use the appropriate tools and procedures of statistical analysis and interpret the results and make them a critical assessment.	ZN1_1A_U01, ZN1_1A_U02, ZN1_1A_U09, ZN1_1A_U13, ZN1_1A_U15, ZN1_1A_U17	S1A_U01, S1A_U02, S1A_U03, S1A_U04, S1A_U05, S1A_U06, S1A_U07, S1A_U08	C-1, C-2, C-3	T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6	M-1, M-2, M-3	S-1
ZN1_1A_OJ7_U02 Student can apply the results of statistical analysis to make decisions and to solve social and economic problems.	ZN1_1A_U01, ZN1_1A_U02, ZN1_1A_U08, ZN1_1A_U09, ZN1_1A_U11, ZN1_1A_U13, ZN1_1A_U15	S1A_U01, S1A_U02, S1A_U03, S1A_U04, S1A_U05, S1A_U06, S1A_U07, S1A_U08, S1A_U09	C-1, C-2, C-3	T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6, T-W-7	M-1, M-2, M-3	S-1

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
ZN1_1A_OJ7_K01 The student has mastered the principles of individual work and teamwork.	ZN1_1A_K02, ZN1_1A_K03, ZN1_1A_K05, ZN1_1A_K09	S1A_K02, S1A_K03, S1A_K04, S1A_K05	C-1, C-2, C-3	T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6, T-W-7	M-1, M-2, M-3	S-1

Kryterium oceny - wiedza

Efekt kształcenia	Ocena	Kryterium oceny
ZN1_1A_OJ7_W01 The student knows the basic concepts and methods of analysis used in statistics and selected methods of statistical inference.	2,0	The student knows the basic concepts and methods of analysis used in statistics and selected methods of statistical inference.
	3,0	The student knows some of the basic concepts and methods of analysis used in statistics and a few methods of statistical inference.
	3,5	The student knows most of the basic concepts and methods of analysis used in statistics and a few methods of statistical inference.
	4,0	The student knows most of the basic concepts and methods of analysis used in statistics and most of the required methods of statistical inference.
	4,5	The student knows the basic concepts and methods of analysis used in statistics and most of the required methods of statistical inference.
	5,0	The student knows the basic concepts and methods of analysis used in statistics and selected statistical inference methods and knows how to use knowledge to solve social and economic problems.
ZN1_1A_OJ7_W02 The student knows the popular statistical packages, and knows how to leverage their statistical knowledge to solve problems of socio-economic issues.	2,0	The student does not know the statistical packages and does not know how to leverage their statistical knowledge to solve problems of socio-economic issues.
	3,0	The student knows the correct number of modules known statistical packages and knows (with the help of the teacher) how to leverage their statistical knowledge to solve problems of socio-economic issues.
	3,5	The student knows all the modules of known statistical packages and knows (with the help of the teacher) how to leverage their statistical knowledge to solve (indicated by the teacher), the tasks of socio-economic issues.
	4,0	The student knows all the modules of known statistical packages and knows how to leverage their statistical knowledge to solve (indicated by the teacher), the tasks of socio-economic issues.
	4,5	The student knows all the modules of known statistical packages and knows how to leverage their statistical knowledge to solve tasks independently proposed a socio-economic issues.
	5,0	The student can independently propose the use of appropriate statistical tools, is able to evaluate their suitability for testing the correctness of the structure, dependencies and dynamics of socio-economic, socio-economic phenomena, knows how to use all modules of known statistical packages.

Kryterium oceny - umiejętności

Efekt kształcenia	Ocena	Kryterium oceny
ZN1_1A_OJ7_U01 Students can formulate the problem using statistical concepts, use the appropriate tools and procedures of statistical analysis and interpret the results and make them a critical assessment.	2,0	The student is not able to formulate the problem and apply the appropriate tools and procedures for statistical analysis and interpret the obtained results and make them a critical assessment.
	3,0	Student can, with the help of the teacher, formulate the problem and apply several tools and procedures for statistical analysis.
	3,5	Student can, with the help of the teacher, formulate the problem and apply most of the tools and procedures for statistical analysis.
	4,0	Student can formulate the problem and apply the tools and procedures for statistical analysis.
	4,5	Student can formulate the problem using statistical concepts, use the appropriate tools and procedures and interpret statistical analysis (with the help of the teacher) received their results and make a critical assessment.
	5,0	Student can formulate the problem using statistical concepts, use the appropriate tools and procedures of statistical analysis and interpret the results and make them a critical assessment.
ZN1_1A_OJ7_U02 Student can apply the results of statistical analysis to make decisions and to solve social and economic problems.	2,0	Student can not apply the results of statistical analysis to make decisions and to solve social and economic problems.
	3,0	Student can apply (with the help of the teacher) the results of statistical analysis to make a decision.
	3,5	Student can apply the results of statistical analysis to make decisions.
	4,0	Student can apply the results of statistical analysis to make decisions and to solve (indicated by the teacher), socio-economic problems.
	4,5	Student can apply the results of statistical analysis to make decisions and attempts to solve the socioeconomic problems.
	5,0	Student can apply the results of statistical analysis to make decisions and solve social and economic problems.

Kryterium oceny - inne kompetencje społeczne i personalne

Efekt kształcenia	Ocena	Kryterium oceny
ZN1_1A_OJ7_K01 The student has mastered the principles of individual work and teamwork.	2,0	Student had not mastered the principles of individual work and teamwork.
	3,0	Student can conduct a statistical survey of the individual alone, and a teacher to organize a group research project.
	3,5	Student can perform independently the individual surveys and organize a group research project supported by the teacher.
	4,0	Student has mastered the principles of individual work and teamwork, can independently organize and carry out individual or group research project, with the help of the teacher to identify methods and tools needed to solve a defined problem and an initial analysis of the results.
	4,5	Student has mastered the principles of individual work and teamwork, can independently organize and carry out individual or group research project to identify methods and tools needed to solve a defined problem and make a comprehensive analysis of the results.
	5,0	Student has mastered the principles of individual work and teamwork, can independently organize and carry out individual or group research project to identify methods and tools needed to solve a defined problem, make a comprehensive analysis of the results, use all modules of known statistical packages.

Literatura podstawowa

Ramsey J. B., The Elements of Statistics with Applications to Economics and the Social Sciences, South-Western College Pub, 2001
Gentle J. E., Elements of Computational Statistics, Springer, 2005
Hastie T., Tibshirani R., Friedman J., The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer, 2009

Literatura dodatkowa

Hill T., Lewicki T., STATISTICS Methods and Applications, Statsoft, 2008

Treści programowe - wykłady

KOD	Treść programowa	Godziny
T-W-1	Introduction to statistics. Basic notions. Data sources. Different Types of Data. Examples of applications of statistics.	4
T-W-2	Summary descriptive measures. Descriptive methods and exploratory data analysis. Graphical presentation of data. Numerical measures of center, dispersion and asymmetry.	5
T-W-3	Basic notions of probability theory. Random variable and its distribution.	4
T-W-4	Estimation of population parameters. Estimator and its properties. Standard error of estimation. Confidence intervals.	4
T-W-5	Testing statistical hypothesis. Parametric significance tests. Chi-square test. One-way ANOVA F test.	4
T-W-6	Regression and correlation analysis. Two-dimensional distributions. Contingency tables and chi-square test for independence. Significance tests for Spearman’s and Pearson’s correlation coefficients. Simple linear regression model. Testing the signi-ficance of the structural parameters.	5
T-W-7	Index numbers. Average growth rate.	4
		30

Formy aktywności - wykłady

KOD	Forma aktywności	Godziny
A-W-1	Participation in lectures	30
A-W-2	Participation in the consultation	30
A-W-3	The study of literature	20
A-W-4	Develop formulas	10
A-W-5	Implementation of housework	28
A-W-6	Preparing for the Exam	30
A-W-7	Participation in the exam	2
		150

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

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	ZN1_1A_OJ7_W01	The student knows the basic concepts and methods of analysis used in statistics and selected methods of statistical inference.
Odniesienie do efektów kształcenia dla kierunku studiów	ZN1_1A_W01	ma podstawową wiedzę na temat ekonomii i zarządzania, ich miejscu w naukach społecznych i powiązań z innymi dyscyplinami naukowymi
	ZN1_1A_W06	ma elementarną wiedzę o ludziach jako podmiotach tworzących strukturę organizacyjną oraz zna podstawowe pojęcia, prawidłowości i problemy kierowania ludźmi w organizacjach
	ZN1_1A_W07	objaśnia znaczenie i sposoby gromadzenia informacji na potrzeby zarządzania organizacjami
Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	S1A_W01	ma podstawową wiedzę o charakterze nauk społecznych, ich miejscu w systemie nauk i relacjach do innych nauk
	S1A_W05	ma podstawową wiedzę o człowieku, w szczególności jako podmiocie konstytuującym struktury społeczne i zasady ich funkcjonowania, a także działającym w tych strukturach
	S1A_W06	zna metody i narzędzia, w tym techniki pozyskiwania danych, właściwe dla dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów, pozwalające opisywać struktury i instytucje społeczne oraz procesy w nich i między nimi zachodzące
Cel przedmiotu	C-1	The objective of the course is to provide students with knowledge on the basic descriptive methods and inferential statistics. The acquired knowledge should serve as a basis for further advanced courses.
	C-2	During the course the students get familiar with basic methods of descriptive statistics and statistical inference. These methods are intended to provide tools for decision making under uncertainty, using sample data.
	C-3	The course contains an overview of graphical and numerical methods for summarizing data as well as basic notions of inferential statistics, including basic distributions, estimation theory, confidence intervals, statistical hypothesis testing, simple linear regression, and index numbers.
Treści programowe	T-W-1	Introduction to statistics. Basic notions. Data sources. Different Types of Data. Examples of applications of statistics.
	T-W-2	Summary descriptive measures. Descriptive methods and exploratory data analysis. Graphical presentation of data. Numerical measures of center, dispersion and asymmetry.
	T-W-3	Basic notions of probability theory. Random variable and its distribution.
	T-W-4	Estimation of population parameters. Estimator and its properties. Standard error of estimation. Confidence intervals.
	T-W-5	Testing statistical hypothesis. Parametric significance tests. Chi-square test. One-way ANOVA F test.
	T-W-6	Regression and correlation analysis. Two-dimensional distributions. Contingency tables and chi-square test for independence. Significance tests for Spearman’s and Pearson’s correlation coefficients. Simple linear regression model. Testing the signi-ficance of the structural parameters.
	T-W-7	Index numbers. Average growth rate.
Metody nauczania	M-1	Informational lecture - illustrated with slides and examples of a practical nature in a chosen utility environment, discussion about solutions from literature and practice.
	M-2	Classes based on solving problems and practical standard exercises.
	M-3	Students use handbooks, statistical tables and statistical software.
Sposób oceny	S-1	Ocena podsumowująca: The final exam has a written form and consists of two parts: standard exercises and a test.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student knows the basic concepts and methods of analysis used in statistics and selected methods of statistical inference.
	3,0	The student knows some of the basic concepts and methods of analysis used in statistics and a few methods of statistical inference.
	3,5	The student knows most of the basic concepts and methods of analysis used in statistics and a few methods of statistical inference.
	4,0	The student knows most of the basic concepts and methods of analysis used in statistics and most of the required methods of statistical inference.
	4,5	The student knows the basic concepts and methods of analysis used in statistics and most of the required methods of statistical inference.
	5,0	The student knows the basic concepts and methods of analysis used in statistics and selected statistical inference methods and knows how to use knowledge to solve social and economic problems.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	ZN1_1A_OJ7_W02	The student knows the popular statistical packages, and knows how to leverage their statistical knowledge to solve problems of socio-economic issues.
Odniesienie do efektów kształcenia dla kierunku studiów	ZN1_1A_W06	ma elementarną wiedzę o ludziach jako podmiotach tworzących strukturę organizacyjną oraz zna podstawowe pojęcia, prawidłowości i problemy kierowania ludźmi w organizacjach
Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	S1A_W05	ma podstawową wiedzę o człowieku, w szczególności jako podmiocie konstytuującym struktury społeczne i zasady ich funkcjonowania, a także działającym w tych strukturach
Cel przedmiotu	C-1	The objective of the course is to provide students with knowledge on the basic descriptive methods and inferential statistics. The acquired knowledge should serve as a basis for further advanced courses.
	C-2	During the course the students get familiar with basic methods of descriptive statistics and statistical inference. These methods are intended to provide tools for decision making under uncertainty, using sample data.
	C-3	The course contains an overview of graphical and numerical methods for summarizing data as well as basic notions of inferential statistics, including basic distributions, estimation theory, confidence intervals, statistical hypothesis testing, simple linear regression, and index numbers.
Treści programowe	T-W-1	Introduction to statistics. Basic notions. Data sources. Different Types of Data. Examples of applications of statistics.
	T-W-2	Summary descriptive measures. Descriptive methods and exploratory data analysis. Graphical presentation of data. Numerical measures of center, dispersion and asymmetry.
	T-W-3	Basic notions of probability theory. Random variable and its distribution.
	T-W-4	Estimation of population parameters. Estimator and its properties. Standard error of estimation. Confidence intervals.
	T-W-5	Testing statistical hypothesis. Parametric significance tests. Chi-square test. One-way ANOVA F test.
	T-W-6	Regression and correlation analysis. Two-dimensional distributions. Contingency tables and chi-square test for independence. Significance tests for Spearman’s and Pearson’s correlation coefficients. Simple linear regression model. Testing the signi-ficance of the structural parameters.
	T-W-7	Index numbers. Average growth rate.
Metody nauczania	M-2	Classes based on solving problems and practical standard exercises.
Metody nauczania	M-3	Students use handbooks, statistical tables and statistical software.
Sposób oceny	S-1	Ocena podsumowująca: The final exam has a written form and consists of two parts: standard exercises and a test.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student does not know the statistical packages and does not know how to leverage their statistical knowledge to solve problems of socio-economic issues.
	3,0	The student knows the correct number of modules known statistical packages and knows (with the help of the teacher) how to leverage their statistical knowledge to solve problems of socio-economic issues.
	3,5	The student knows all the modules of known statistical packages and knows (with the help of the teacher) how to leverage their statistical knowledge to solve (indicated by the teacher), the tasks of socio-economic issues.
	4,0	The student knows all the modules of known statistical packages and knows how to leverage their statistical knowledge to solve (indicated by the teacher), the tasks of socio-economic issues.
	4,5	The student knows all the modules of known statistical packages and knows how to leverage their statistical knowledge to solve tasks independently proposed a socio-economic issues.
	5,0	The student can independently propose the use of appropriate statistical tools, is able to evaluate their suitability for testing the correctness of the structure, dependencies and dynamics of socio-economic, socio-economic phenomena, knows how to use all modules of known statistical packages.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	ZN1_1A_OJ7_U01	Students can formulate the problem using statistical concepts, use the appropriate tools and procedures of statistical analysis and interpret the results and make them a critical assessment.
Odniesienie do efektów kształcenia dla kierunku studiów	ZN1_1A_U01	potrafi stosować zdobytą wiedzą naukową do interpretacji zjawisk społecznych
	ZN1_1A_U02	jest przygotowany do realizacji podstawowych funkcji zarządzania
	ZN1_1A_U09	potrafi rozwiązywać problemy związane z zarządzaniem zasobami ludzkimi
	ZN1_1A_U13	potrafi określić źródła finansowania i posiada umiejętność wykorzystania wiedzy z rachunkowości w zarządzaniu
	ZN1_1A_U15	potrafi prognozować procesy i zjawiska społeczne z wykorzystaniem standardowych metod badawczych
	ZN1_1A_U17	wykorzystuje zdobytą wiedzę do rozstrzygania dylematów pojawiających się w pracy zawodowej
Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	S1A_U01	potrafi prawidłowo interpretować zjawiska społeczne (kulturowe, polityczne, prawne, ekonomiczne) w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U02	potrafi wykorzystać podstawową wiedzę teoretyczną i pozyskiwać dane do analizowania konkretnych procesów i zjawisk społecznych (kulturowych, politycznych, prawnych, gospodarczych) w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U03	potrafi właściwie analizować przyczyny i przebieg konkretnych procesów i zjawisk społecznych (kulturowych, politycznych, prawnych, gospodarczych) w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U04	potrafi prognozować procesy i zjawiska społeczne (kulturowe, polityczne, prawne, ekonomiczne) z wykorzystaniem standardowych metod i narzędzi w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U05	prawidłowo posługuje się systemami normatywnymi oraz wybranymi normami i regułami (prawnymi, zawodowymi, moralnymi) w celu rozwiązania konkretnego zadania z zakresu dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U06	wykorzystuje zdobytą wiedzę do rozstrzygania dylematów pojawiających się w pracy zawodowej
	S1A_U07	analizuje proponowane rozwiązania konkretnych problemów i proponuje, w tym zakresie odpowiednie rozstrzygnięcia
	S1A_U08	posiada umiejętność rozumienia i analizowania zjawisk społecznych
Cel przedmiotu	C-1	The objective of the course is to provide students with knowledge on the basic descriptive methods and inferential statistics. The acquired knowledge should serve as a basis for further advanced courses.
	C-2	During the course the students get familiar with basic methods of descriptive statistics and statistical inference. These methods are intended to provide tools for decision making under uncertainty, using sample data.
	C-3	The course contains an overview of graphical and numerical methods for summarizing data as well as basic notions of inferential statistics, including basic distributions, estimation theory, confidence intervals, statistical hypothesis testing, simple linear regression, and index numbers.
Treści programowe	T-W-1	Introduction to statistics. Basic notions. Data sources. Different Types of Data. Examples of applications of statistics.
	T-W-2	Summary descriptive measures. Descriptive methods and exploratory data analysis. Graphical presentation of data. Numerical measures of center, dispersion and asymmetry.
	T-W-3	Basic notions of probability theory. Random variable and its distribution.
	T-W-4	Estimation of population parameters. Estimator and its properties. Standard error of estimation. Confidence intervals.
	T-W-5	Testing statistical hypothesis. Parametric significance tests. Chi-square test. One-way ANOVA F test.
	T-W-6	Regression and correlation analysis. Two-dimensional distributions. Contingency tables and chi-square test for independence. Significance tests for Spearman’s and Pearson’s correlation coefficients. Simple linear regression model. Testing the signi-ficance of the structural parameters.
Metody nauczania	M-1	Informational lecture - illustrated with slides and examples of a practical nature in a chosen utility environment, discussion about solutions from literature and practice.
	M-2	Classes based on solving problems and practical standard exercises.
	M-3	Students use handbooks, statistical tables and statistical software.
Sposób oceny	S-1	Ocena podsumowująca: The final exam has a written form and consists of two parts: standard exercises and a test.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	The student is not able to formulate the problem and apply the appropriate tools and procedures for statistical analysis and interpret the obtained results and make them a critical assessment.
	3,0	Student can, with the help of the teacher, formulate the problem and apply several tools and procedures for statistical analysis.
	3,5	Student can, with the help of the teacher, formulate the problem and apply most of the tools and procedures for statistical analysis.
	4,0	Student can formulate the problem and apply the tools and procedures for statistical analysis.
	4,5	Student can formulate the problem using statistical concepts, use the appropriate tools and procedures and interpret statistical analysis (with the help of the teacher) received their results and make a critical assessment.
	5,0	Student can formulate the problem using statistical concepts, use the appropriate tools and procedures of statistical analysis and interpret the results and make them a critical assessment.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	ZN1_1A_OJ7_U02	Student can apply the results of statistical analysis to make decisions and to solve social and economic problems.
Odniesienie do efektów kształcenia dla kierunku studiów	ZN1_1A_U01	potrafi stosować zdobytą wiedzą naukową do interpretacji zjawisk społecznych
	ZN1_1A_U02	jest przygotowany do realizacji podstawowych funkcji zarządzania
	ZN1_1A_U08	potrafi zarządzać projektami
	ZN1_1A_U09	potrafi rozwiązywać problemy związane z zarządzaniem zasobami ludzkimi
	ZN1_1A_U11	posługuje się technologiami informacyjno-komunikacyjnymi wspomagającymi proces podejmowania decyzji
	ZN1_1A_U13	potrafi określić źródła finansowania i posiada umiejętność wykorzystania wiedzy z rachunkowości w zarządzaniu
	ZN1_1A_U15	potrafi prognozować procesy i zjawiska społeczne z wykorzystaniem standardowych metod badawczych
Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	S1A_U01	potrafi prawidłowo interpretować zjawiska społeczne (kulturowe, polityczne, prawne, ekonomiczne) w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U02	potrafi wykorzystać podstawową wiedzę teoretyczną i pozyskiwać dane do analizowania konkretnych procesów i zjawisk społecznych (kulturowych, politycznych, prawnych, gospodarczych) w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U03	potrafi właściwie analizować przyczyny i przebieg konkretnych procesów i zjawisk społecznych (kulturowych, politycznych, prawnych, gospodarczych) w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U04	potrafi prognozować procesy i zjawiska społeczne (kulturowe, polityczne, prawne, ekonomiczne) z wykorzystaniem standardowych metod i narzędzi w zakresie dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U05	prawidłowo posługuje się systemami normatywnymi oraz wybranymi normami i regułami (prawnymi, zawodowymi, moralnymi) w celu rozwiązania konkretnego zadania z zakresu dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów
	S1A_U06	wykorzystuje zdobytą wiedzę do rozstrzygania dylematów pojawiających się w pracy zawodowej
	S1A_U07	analizuje proponowane rozwiązania konkretnych problemów i proponuje, w tym zakresie odpowiednie rozstrzygnięcia
	S1A_U08	posiada umiejętność rozumienia i analizowania zjawisk społecznych
	S1A_U09	posiada umiejętność przygotowania typowych prac pisemnych w języku polskim i języku obcym, uznawanym za podstawowy dla dziedzin nauki i dyscyplin naukowych, właściwych dla studiowanego kierunku studiów, dotyczących zagadnień szczegółowych, z wykorzystaniem podstawowych ujęć teoretycznych, a także różnych źródeł
Cel przedmiotu	C-1	The objective of the course is to provide students with knowledge on the basic descriptive methods and inferential statistics. The acquired knowledge should serve as a basis for further advanced courses.
	C-2	During the course the students get familiar with basic methods of descriptive statistics and statistical inference. These methods are intended to provide tools for decision making under uncertainty, using sample data.
	C-3	The course contains an overview of graphical and numerical methods for summarizing data as well as basic notions of inferential statistics, including basic distributions, estimation theory, confidence intervals, statistical hypothesis testing, simple linear regression, and index numbers.
Treści programowe	T-W-1	Introduction to statistics. Basic notions. Data sources. Different Types of Data. Examples of applications of statistics.
	T-W-2	Summary descriptive measures. Descriptive methods and exploratory data analysis. Graphical presentation of data. Numerical measures of center, dispersion and asymmetry.
	T-W-3	Basic notions of probability theory. Random variable and its distribution.
	T-W-4	Estimation of population parameters. Estimator and its properties. Standard error of estimation. Confidence intervals.
	T-W-5	Testing statistical hypothesis. Parametric significance tests. Chi-square test. One-way ANOVA F test.
	T-W-6	Regression and correlation analysis. Two-dimensional distributions. Contingency tables and chi-square test for independence. Significance tests for Spearman’s and Pearson’s correlation coefficients. Simple linear regression model. Testing the signi-ficance of the structural parameters.
	T-W-7	Index numbers. Average growth rate.
Metody nauczania	M-1	Informational lecture - illustrated with slides and examples of a practical nature in a chosen utility environment, discussion about solutions from literature and practice.
	M-2	Classes based on solving problems and practical standard exercises.
	M-3	Students use handbooks, statistical tables and statistical software.
Sposób oceny	S-1	Ocena podsumowująca: The final exam has a written form and consists of two parts: standard exercises and a test.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	Student can not apply the results of statistical analysis to make decisions and to solve social and economic problems.
	3,0	Student can apply (with the help of the teacher) the results of statistical analysis to make a decision.
	3,5	Student can apply the results of statistical analysis to make decisions.
	4,0	Student can apply the results of statistical analysis to make decisions and to solve (indicated by the teacher), socio-economic problems.
	4,5	Student can apply the results of statistical analysis to make decisions and attempts to solve the socioeconomic problems.
	5,0	Student can apply the results of statistical analysis to make decisions and solve social and economic problems.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	ZN1_1A_OJ7_K01	The student has mastered the principles of individual work and teamwork.
Odniesienie do efektów kształcenia dla kierunku studiów	ZN1_1A_K02	jest przygotowany do samodzielnej pracy oraz pracy w zespole (słuchanie, negocjacje, perswazja, prezentacja)
	ZN1_1A_K03	jest przygotowany do określania priorytetów służących do realizacji zadań ustalonych przez siebie lub innych
	ZN1_1A_K05	jest przygotowany do opracowywania projektów społecznych uwzględniających aspekty prawne, ekonomiczne i polityczne
	ZN1_1A_K09	jest przygotowany do podejmowania odpowiedzialności za swoje zadania oraz zespołu, którym kieruje
Odniesienie do efektów zdefiniowanych dla obszaru kształcenia	S1A_K02	potrafi współdziałać i pracować w grupie, przyjmując w niej różne role
	S1A_K03	potrafi odpowiednio określić priorytety służące realizacji określonego przez siebie lub innych zadania
	S1A_K04	prawidłowo identyfikuje i rozstrzyga dylematy związane z wykonywaniem zawodu
	S1A_K05	umie uczestniczyć w przygotowaniu projektów społecznych (politycznych, gospodarczych, obywatelskich) uwzględniając aspekty prawne, ekonomiczne i polityczne
Cel przedmiotu	C-1	The objective of the course is to provide students with knowledge on the basic descriptive methods and inferential statistics. The acquired knowledge should serve as a basis for further advanced courses.
	C-2	During the course the students get familiar with basic methods of descriptive statistics and statistical inference. These methods are intended to provide tools for decision making under uncertainty, using sample data.
	C-3	The course contains an overview of graphical and numerical methods for summarizing data as well as basic notions of inferential statistics, including basic distributions, estimation theory, confidence intervals, statistical hypothesis testing, simple linear regression, and index numbers.
Treści programowe	T-W-1	Introduction to statistics. Basic notions. Data sources. Different Types of Data. Examples of applications of statistics.
	T-W-2	Summary descriptive measures. Descriptive methods and exploratory data analysis. Graphical presentation of data. Numerical measures of center, dispersion and asymmetry.
	T-W-3	Basic notions of probability theory. Random variable and its distribution.
	T-W-4	Estimation of population parameters. Estimator and its properties. Standard error of estimation. Confidence intervals.
	T-W-5	Testing statistical hypothesis. Parametric significance tests. Chi-square test. One-way ANOVA F test.
	T-W-6	Regression and correlation analysis. Two-dimensional distributions. Contingency tables and chi-square test for independence. Significance tests for Spearman’s and Pearson’s correlation coefficients. Simple linear regression model. Testing the signi-ficance of the structural parameters.
	T-W-7	Index numbers. Average growth rate.
Metody nauczania	M-1	Informational lecture - illustrated with slides and examples of a practical nature in a chosen utility environment, discussion about solutions from literature and practice.
	M-2	Classes based on solving problems and practical standard exercises.
	M-3	Students use handbooks, statistical tables and statistical software.
Sposób oceny	S-1	Ocena podsumowująca: The final exam has a written form and consists of two parts: standard exercises and a test.
Kryteria oceny	Ocena	Kryterium oceny
	2,0	Student had not mastered the principles of individual work and teamwork.
	3,0	Student can conduct a statistical survey of the individual alone, and a teacher to organize a group research project.
	3,5	Student can perform independently the individual surveys and organize a group research project supported by the teacher.
	4,0	Student has mastered the principles of individual work and teamwork, can independently organize and carry out individual or group research project, with the help of the teacher to identify methods and tools needed to solve a defined problem and an initial analysis of the results.
	4,5	Student has mastered the principles of individual work and teamwork, can independently organize and carry out individual or group research project to identify methods and tools needed to solve a defined problem and make a comprehensive analysis of the results.
	5,0	Student has mastered the principles of individual work and teamwork, can independently organize and carry out individual or group research project to identify methods and tools needed to solve a defined problem, make a comprehensive analysis of the results, use all modules of known statistical packages.