UČNI NAČRT PREDMETA / COURSE SYLLABUS 2014/2015 Statistika Statistics Predmet: Course Title: Študijski program Study programme UNI-Ekonomske in poslovne vede UNI-Economic and business sciences Študijska smer Study field Letnik Year Semester Semester vse 2. 3. Obvezni Vrsta predmeta/ Course type: Univerzitetna koda predmeta / University subject code: Predavanja Lectures Seminar Seminar Sem. vaje Tutorial 45 15 Nosilec predmeta / Lecturer: Jeziki: S/A Languages: S/E Lab. vaje Labor work 15 Teren. vaje Field work Samost. delo Individ. work 75 ECTS 5 Kavkler A. – 1.del (the first part) ,Tominc P. – 2.del (the second part) Predavanja / Lecture: Vaje / Tutorial: Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti: Prerequisits: Vsebina: Vsebina 1. dela predmeta: Osnove verjetnostnega računa: poskusi in dogodki, operacije z dogodki, statistična in klasična definicija verjetnosti, verjetnost produkta, Bernoullijeva formula. Empirične porazdelitve: frekvenčne porazdelitve, aritmetična sredina, vzorčna varianca, vzorčni momenti. Diskretne in zvezne porazdelitve: definicija in osnovni pojmi, porazdelitvena funkcija, matematično upanje, varianca, momenti, pomembnejše porazdelitve (binomska, Poissonova, hipergeometrijska, normalna, 2 - porazdelitev, t – porazdelitev, F – porazdelitev). Osnove vzorčenja in testiranje statističnih domnev: končna in neskončna statistična mnoţica, cenilke in ocene parametrov, intervalsko ocenjevanje parametrov, napake 1. in 2. vrste, 2 - test, u – test, t – test, F – Content (Syllabus outline): Content of the first part Probability theory basics: trials and events, event operations, statstical and classical definition of probability, product probability, Bernoulli formula. Empirical distributions: frequency distributions, arithmetic mean, sample variance, sample moments. Discrete and continuous distributions: definition and basic notions, distribution function, mean, variance, moments, important distributions (binomial, Poisson, hypergeometric, normal, 2 distribution, t – distribution and F – distribution). Sampling and hypothesis testing: finite and infinite statistical set, statistics and parameter estimation, interval parameter estimates, type I error and type II error, 2 - test, u – test, t – test, F – test. Statistical software: SPSS. Economic applications are included in most chapters. test. Uporaba statistične programske opreme: SPSS. Vsebina 2. dela predmeta: zbiranje podatkov prikazovanje podatkov v tabelah in grafih relativna števila (indeksi) Srednje vrednosti, mere variabilnosti, asimetrije in sploščenosti Intervalno ocenjevanje vrednosti statističnih parametrov in osnove preizkušanja domnev o statističnih parametrih Osnove enostavne regresije Osnove analize in napovedovanja vrednosti v časovnih vrstah. Uporaba SPSS in Excella Content of the second part: Data-collection Graphs and table constructions Relative numbers (indices) Measures of central tendency, measures of dispersion, skewness and curtosis Estimation and basics of hypothesis testing Basics of simple regression Basics of the time series analysis and forecasting Use of software package (SPSS) and the use of Excel. Temeljni literatura in viri / Textbooks: del predmeta - The first part: S. Indihar, I. Kavkler, M. Mastinšek, Matematika za ekonomiste, 1. del, EPF, Maribor, 2002. A. Kavkler, I. Kavkler. Zapiski predavanj pri predmetu Statistika, 1. del. EPF, 2014. A. Kavkler. Gradivo za vaje pri predmetu Statistika, 1. del. EPF, 2014. J. Marovt, Statistika (1. del predmeta), Učno gradivo pri predmetu Statistika (1. del predmeta), interno gradivo, EPF, 2008. G. Keller, B. Warrack, Statistics for Management and Economics, Thomson Learning, London, 2000. J. Marovt, Gradivo pri predmetu Statistika: praktikum iz osnov verjetnostnega računa, EPF, Maribor, 2010 del predmeta – The second part Tominc Polona: Statistika (2. del predmeta), Učno gradivo pri predmetu Statistika (2. del predmeta), interno gradivo, EPF, 2007/2008 Izbrana poglavja iz (Selected chapters) Groebner, Shannon, Fry, Smith: Business statistics – a decision-making approach, Pearson Prentice Hall, 2001, 2005. Cilji in kompetence: Študenti: 1. Spoznajo uporabnost statističnih metod pri reševanju poslovnih problemov. 2. Utrdijo in nadgradijo teoretično znanje na področju statističnih tehnik in metod, ki omogočajo spremeniti različne podatke v uporabne informacije za poslovno odločanje. 3. Osvojijo analitičen matematično statističen pristop k preučevanju poslovnih problemov, ki se sestoji iz korakov: - formulacija problema na statističen način - izbira ustrezne statistične metode - reševanje problema - interpretacija rezultatov v smislu moţnih rešitev problema. Predvideni študijski rezultati: Objectives: Students: 1. Are familiarised with the applicability of statistical methods for business problems. 2. Enhance their theoretical knowledge in the field of of statistical techniques and methods with the purpose to be able to develop different data into useful information for business decision making. 3. Acquire analytical mathematical-statistical approach to analysis of business problems, consisting of: - Formulate the problem in terms of statistics. - Identify the appropriate statistical techniques. - Solve the problem. - Interpret the results (what the solution means for the problem at hand). Intended learning outcomes: Znanje in razumevanje: Študenti: 1. Osvojijo osnovne pojme deskriptivne in matematične statistike. 2. Se naučijo uporabljati statistične metode pri reševanju poslovnih problemov. 3. Se zavedajo etičnih vprašanj na področju statistične analize. 4. Etična vprašanja znajo uskladiti z lastnimi pogledi. Development of knowledge and understanding: Students: 1. Understand basic concepts of .descriptive and mathematical statistics. 2. Learn to apply statistical methods in solving business problems. 3. Can demonstrate awareness of ethical issues in the field of statistical analysis. 4. Are able to discuss ethical issues in relation to personal beliefs and values. Kognitivne/Intelektualne veščine Študenti: 1. Ob upoštevanju navodil znajo izvesti osnovno analizo, upoštevajoč določena izhodišča. 2. Znajo zbrati in urediti podatke in ideje na standarden način. 3. Znajo presoditi o zanesljivosti podatkov na osnovi znanih metod in po navodilih. 4. Študenti se oblikujejo kot samostojno misleči in v reševanje problemov usmerjeni ljudje. Cognitive/Intellectual skills: Students: 1. Can analyse with guidance using given classification/principles. 2. Can collect and arrange data and ideas in a standard way. 3. Can evaluate the reliability of data using defined techniques and under guidance. 4. Students develop greater independence of thought and the ability to solve problems. Ključne/prenosljive veščine in spretnosti Študenti: 1. Uporabljajo IKT. 2. Razvijajo spretnosti za timsko delo. 3. Izgrajujejo profesionalno etiko. 4. Razvijajo študijske tehnike in strategije za samoizobraţevanje, stalno refleksijo in evalvacijo. 5. Razvijajo interes za vseţivljenjsko učenje. Key/Transferable skills Students: 1. Use ICT. 2. Develop skills for team work. 3. Develop professional ethics. 4. Develop learning techniques and strategies for individual study, permanent reflection and evaluation. 5. Develop interest for lifelong learning. Metode poučevanja in učenja: Learning and teaching methods: predavanja; lectures; AV predstavitve; AV presentations; obravnava študijskih primerov; case studies; aktivno individulano in skupinsko delo active individual and group work Delež (v %) / Načini ocenjevanja: Weight (in %): Assessment: - aktivno delo na predavanjih in 20% -active participation in class discussions; vajah; - pisni izpit 80% -seminar research work; Študent lahko pisni izpit -written examination or 2 tests nadomesti z dvema vmesnima testoma The exam is passed when 44 out of 80 Študent opravi izpit, če na points are obtained by written axam AND pisnem delu (ali na obeh testih at the same time, the sum together with skupaj) zbere najmanj 44 točk points obtained by the active participation od 80-ih moţnih, hkrati pa in class, equals at least 56 points (out of skupaj s točkami aktivnega dela all 100). zbere najmanj 56 točk (od skupnih 100 točk). Reference nosilca / Lecturer's references: KAVKLER, Alenka, FESTIĆ, Mejra. Smooth transition regression model for Slovene stock exchange index returns. Econ. Comput. Econ. Cybern. Stud. Res., 2010, vol. 44, no. 1, str. 147-164. KAVKLER, Alenka, DANACICA, Daniela-Emanuela, BABUCEA, Ana Gabriela, BIĆANIĆ, Ivo, BÖHM, Bernhard, TEVDOVSKI, Dragan, TOŠEVSKA, Katerina, BORŠIČ, Darja. Cox regression models for unemployment duration in Romania, Austria, Slovenia, Croatia, and Macedonia. Rom. J. Econ. Forecast., 2009, 2, str. 81-104. DAJČMAN, Silvo, KAVKLER, Alenka. A comparative DCC-GARCH and rolling wavelet correlation analysis of interdependence between the Slovenian and European stock markets. Econ. Comput. Econ. Cybern. Stud. Res., 2011, vol. 45, no. 4, str. 99-118. FESTIĆ, Mejra, KAVKLER, Alenka. The roots of the banking crisis in the new EU member states : a panel regression approach. Rom. J. Econ. Forecast., 2012, vol. 15, iss. 1, str. 20-40. KAVKLER, Alenka, BORŠIČ, Darja, BEKŐ, Jani. PPP in Central and Eastern European economies : further evidence from panel unite root tests. Appl. econ. lett. (Print), 2012, vol. 19, iss. 16, str. 1543-1548, doi: 10.1080/13504851.2011.637891. FESTIĆ, Mejra, REPINA, Sebastijan, KAVKLER, Alenka. The dynamics of energy price movements estimating coal price dynamics with the principal component method = Dinamika gibanja cen energentov in ocena dinamike gibanja cen premoga z metodo glavnih komponent. Journal of energy technology, 2009, vol. 2, iss. 2, str. 19-40. DAJČMAN, Silvo, FESTIĆ, Mejra, KAVKLER, Alenka. Multiscale test of CAPM for three Central and Eastern European stock markets. Journal of business economics and management, 2013, vol. 14, no. 1, str. 54-76. RADONJIČ, Gregor, TOMINC, Polona. Pomen sistema ravnanja z okoljem ISO 14001 za tehnološko posodabljanje proizvodnih podjetij = The role of the environmental management standard ISO 14001 in technological improvements in manufacturing companies. Naše gospod., 2007, letn. 53, št. 3/4, str. 58-70. [COBISS.SI-ID 9156892] TOMINC, Polona, REBERNIK, Miroslav. Growth aspirations and cultural support for entrepreneurship : a comparison of post-socialist countries. Small bus. econ., 2007, vol. 28, no. 2/3, str. [239]-255. [COBISS.SI-ID 9039388] DUH, Mojca, TOMINC, Polona, REBERNIK, Miroslav. The importance of family enterprises in transition economies : Is it overestimated?. East. Europ. econ., 2009, vol. 47, no. 6, str. 22-42, tabele. [COBISS.SI-ID 10101788] TOMINC, Polona, REBERNIK, Miroslav. Connections of entrepreneurial capacity and openness towards innovations with the individual's decision to become an entrepreneur : a case from Slovenia. Soc. econ. (Print), 2010, vol. 32, no. 2, str. [297]-313, doi: 10.1556/SocEc.2010.0002. [COBISS.SI-ID 10519068] MAKOVŠEK, Dejan, TOMINC, Polona, LOGOŢAR, Klavdij. A cost performance analysis of transport infrastructure construction in Slovenia. Transportation (Dordr.), Online FirstT, 29 January 2011, doi: 10.1007/s11116-011-9319-z. [COBISS.SI-ID 10564892]
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