Descriptive Statistics

General data

Course ID:	0300-MS1-1STA#E
Erasmus code / ISCED:	11.201 The subject classification code consists of three to five digits, where the first three represent the classification of the discipline according to the Discipline code list applicable to the Socrates/Erasmus program, the fourth (usually 0) - possible further specification of discipline information, the fifth - the degree of subject determined based on the year of study for which the subject is intended. / (0542) Statistics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Descriptive Statistics
Name in Polish:	Statystyka opisowa-przedmiot oferowany w języku angielskim
Organizational unit:	Faculty of Economics and Management
Course groups:
ECTS credit allocation (and other scores):	(not available) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	English
Type of course:	(in Polish) podstawowe obligatory courses
Requirements:	Mathematics 0300-MS1-1MAT#E
Prerequisites:	Mathematics 0300-MS1-1MAT#E
Mode:	(in Polish) w sali
Short description:	(in Polish) Distributions of numbers and frequencies of 1- and 2-dimensional variables and their classic, positional and mixed parameters. Stochastic relations and their measures. Basics of time series analysis. Measures of dynamics, including individual and aggregate indexes.
Full description:	(in Polish) Educational profile: general academic Form of study: stationary Course type: obligatory, M_2 primary courses Field and discipline of science: field: economic sciences; discipline: economics Year/semester: 1 year/2 semester Prerequisites : 0300-MS1-1MAT#E Mathematics Number of didactic hours: 15 hours - lecture, 30 hours - classes Teaching methods: Traditional lecture conducted with the use of multimedia presentations, practical and activating methods (individual work, group work) The general form of passing the course: passing classes + exam ESTS points: 5 Student workload balance: participation in lectures - 15 hours participation in classes - 30 hours participation in consultations hours - 4 hours doing homework - 10 hours preparation for classes - 15 hours preparation for the test - 25 hours preparation for the exam and participation in the exam - 26 hours The total student workload - 125 hours Quantitative indicators Student workload related to the course: Number of hours / ECTS points requiring direct teacher participation: 50/2 of a practical nature: 84/3,4
Bibliography:	(in Polish) Z. Michna, Statistics, Publishing House of Wrocław University of Economics, Wroclaw 2014. W. Mendenhall, R. J. Beaver, B. M. Beaver, Introduction to probability and statistics, Brooks/Cole, Belmont 2009. D. L. Waller, Statistics for business, Elsevier, Amsterdam 2008. J. T. McClave, P. G. Benson, T. Sincich, Statistics for Business and Economics , Prentice Hall International, New Jersey 2001.
Learning outcomes:	(in Polish) KNOWLEDGE 1STA_W01 Knows the methods of statistical description of one-dimensional empirical distribution (measures of central tendency, measures of dispersion, measures of skewness and concentration). M1_W06 1STA_W02 Knows the methods of statistical description of the relationship between two variables (construction of a correlation table, measures of stochastic and correlation relationships). M1_W06 1STA_W03 Knows the methods of analyzing the development of the phenomenon in time (measures of dynamics, analysis of time series). M1_W06 SKILLS 1STA_U01 Has the ability to choose the appropriate measure for the description of the selected aspect of one-dimensional empirical distribution, the relationship between two variables as well as dynamics of phenomenon, and is able to interpret the measures of descriptive statistics. M1_U02, M1_U09 1STA_U02 Has basic skills of individual analysis and interpretation of quantitative phenomena and processes in various areas of economic and social life (based on the general population). M1_U02, M1_U09 SOCIAL COMPETENCES 1STA Is able to individually expand knowledge and skills in descriptive statistics. K01 M1_K06
Assessment methods and assessment criteria:	(in Polish) The condition of passing the course is to achieve assumed learning outcomes. Assessment methods of lectures: written or oral exam. Students who have completed the classes are allowed to take the exam. Assessment methods of classes: test and activity during the classes. Leaving the student more than 4 hours qualify to fail the subject. Completing the absences takes place during the teacher's consultation hours.

This course is not currently offered.

Course descriptions are protected by copyright.
Copyright by University of Bialystok.