STA Statistics

Institute of Technology and Business in České Budějovice
winter 2016
Extent and Intensity
2/2/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Vladislav Biba, Ph.D. (seminar tutor)
Mgr. Václav Dobiáš (seminar tutor)
Guaranteed by
Mgr. Vladislav Biba, Ph.D.
Department of Informatics and Natural Sciences – Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice
Supplier department: Department of Informatics and Natural Sciences – Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice
Timetable of Seminar Groups
STA/A3: Sun 23. 10. 8:00–9:30 E1, 9:40–11:10 E1, V. Biba
STA/A3a: Sun 23. 10. 14:50–16:20 D216, 16:30–18:00 D216, 18:10–19:40 D216, V. Biba
STA/A3b: Sat 12. 11. 8:00–9:30 D216, 9:40–11:10 D216, 11:25–12:55 D216, V. Biba
STA/A3c: Sat 12. 11. 14:50–16:20 D216, 16:30–18:00 D216, 18:10–19:40 D216, V. Biba
STA/A3d: Sun 13. 11. 8:00–9:30 D216, 9:40–11:10 D216, 11:25–12:55 D216, V. Biba
STA/P01: Thu 13:05–14:35 B1, V. Biba
STA/S01: Thu 9:40–11:10 D216, V. Dobiáš
STA/S02: Thu 11:25–12:55 D216, V. Biba
STA/S03: Tue 14:50–16:20 D216, V. Biba
STA/S04: Tue 18:10–19:40 D216, V. Dobiáš
STA/S05: Thu 14:50–16:20 D216, V. Biba
STA/S06: Tue 11:25–12:55 D216, V. Biba
STA/S07: Thu 11:25–12:55 D215, V. Dobiáš
Prerequisites
MAX_KOMBINOVANYCH(140) && MAX_PREZENCNICH(224)
Knowledge of INF_1 course content is an advantage.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 364 student(s).
Current registration and enrolment status: enrolled: 0/364, only registered: 0/364
fields of study / plans the course is directly associated with
there are 23 fields of study the course is directly associated with, display
Course objectives supported by learning outcomes
The aim of the course is to introduce the students with basic procedures in the field of statictical induction, methods of analysis of qualitative and quantitative features and with time series analysis elements. After the successful completion of the course, the student masters the basic procedures in the field of statistical induction, methods of analysis of qualitative and quantitative features and with time series analysis elements. The student is able to collect, process and present statistical data.
Syllabus
  • 1. Methods of descriptive statistics (basic statistical concepts, statistical investigation phase, frequency distribution table, interval frequency distribution, two-dimensional frequency distribution tables, statistical graphs). 2. Basic statistical parameters and indices (arithmetic mean and median, variance and standard deviation, coefficient of variation, percentiles, the characteristics of the aggregated data, simple and composite indices, price indices). 3.Probability and probability summary and their numerical characteristics (random events and their probabilities, properties of probabilities, independent and conditioned random events and their probability and summary and compound probability, random variable and its probability distribution, mean value and dispersion). 4. Basic probability models (binomial distribution, Poisson and normal, their mean and variance, standard random variable, standard ordinary summary, tables, distribution and quantile functions and their tables). 5. Surveys, a division of selection characteristics and basics of statistical induction (basic and selection file, the importance and types of sample surveys, sample distributions, central limit theorem, characteristics of the sample distribution, selective distribution of diameter and the ratio, point and interval estimates of population mean and the ratio and variance, determination of sample size). 6. Testing of statistical hypotheses (null and alternative hypothesis, significance level test and its determination, identification of the refusal, the critical value test, the test criterion, the choice between two hypotheses, hypothesis about the test of mean, ratio and variance, p-value of the test). 7. Two-Sample tests (test of the hypothesis about compliance of two averages, variances of two shares, testing in small choice files). 8. Further tests and analysis of variance (compliance tests, testing of independence in contingency table, single-factor analysis of variance, the degree of power dependence). 9. Simple linear regression and correlation (causal and non-causal dependence, covariance and correlation, scatter plot, the method of least squares, regression line, correlation coefficient, other types of regression functions). 10. Statistical induction in the regression model (population and sample regression function, estimates of regression coefficients and their properties, the standard errors of regression parameters and their confidence intervals, tests in regression analysis). 11. Multivariate regression and prognostic application of regression (multivariate regression model, the partial regression coefficients and their interpretation, the coefficient of determination, significance tests of the model using regression to predict 12.-13. Introduction to the series (time series and its graph, continuous time series and interval time series, characteristic of time series, trend functions, balancing time series by moving averages).
Literature
    required literature
  • Hindls,R. a kol.: Statistika pro ekonomy. Praha, Professional Publishing 2006, ISBN 80-86946-16-9
  • STUCHLÝ, Jaroslav. Statistické analýzy dat : vysokoškolská učebnice. 1. vyd. České Budějovice: Vysoká škola technická a ekonomická v Českých Budějovicích, 2015, 220 pp. ISBN 978-80-7468-087-8. info
  • MAREK, L. a kol. Statistika v příkladech. Praha: Profesional Publishing 2013. ISBN 978-80-7431-218-5
  • STUCHLÝ, J.: Statistika. Studijní opora pro kombinované studium. VŠTE České Bu-dějovice, 2011 (v elektronické podobě)
    recommended literature
  • Stuchlý,J.: Statistika I. Skripta FM VŠE Praha 1999. ISBN 80-7079-754-1 (i v elektronické podobě)
  • Stuchlý,J.: Statistika II. Skripta FM VŠE Praha 1999. ISBN 80-7079-035-0 (i v elektronické podobě)
  • Jarošová,E-Pecáková,I.: Příklady k předmětu statistika B. Skripta VŠE, Praha 2000. ISBN 80-245-0015-9
  • Stuchlý,J.: Statistické metody pro manažerské rozhodování 2004, kap. II, str. 34-50 (neparametrické testy), FM VŠE v Praze, ISBN 80-245-0153-8 (i v elektronické po-době)
  • HEBÁK, Petr, Diana BÍLKOVÁ a Alžběta SVOBODOVÁ. Praktikum k výuce matematické statistiky II: testování hypotéz. Vyd. 3. V Praze: Oeconomica, 2009, 280 s. ISBN 978-80-245-1574-8.
  • Seger,J.-Hindls,R.: Statistické metody v tržním hospodářství Vicoria Publishing Praha 1995. ISBN 80-7187-058-7
  • Řezanková,H.-Löster,T.: Úvod do statistiky. VŠE v Praze, Nakladatelství Oeconomi-ca, ISBN 978-80-245-1514-4
  • SVATOŠOVÁ, L.-PRÁŠILOVÁ, M. Statistické metody v příkladech. Skriptum Pro-vozně ekonomické fakulty ČZU, Praha 2009, ISBN 978-80-213-1673-7
  • Marek L., Jarošová E., Pecáková I., Pourová Z., Vrabec M. (2005): Statistika pro ekonomy – aplikace, Professional Publishing, Praha. ISBN 80-86419-68-1
  • MAREK, Luboš. Statistika v příkladech. 1. vyd. Praha: Professional Publishing, 2013, 403 s. ISBN 978-80-7431-118-5.
  • Arltová,M.-Bílková,D.-Jarošová,E.-Pourová,Z.: Příklady k předmětu Statistika A. Skripta VŠE, Praha 2001. ISBN 80-245-0178-3
  • Arltová, M., Bílková, D., Čenčík, P., Jarošová, E., Pecáková, I., Pourová, Z.: Základy statistiky v příkladech. Tribun EU, 192 str., 2014. ISBN 978-80-263-0756-3
    not specified
  • Kerns, G. J.: Introduction to Probability and Statistics Using R, 2010, ISBN 978-0-557-24979-4 (available online)
  • Montgomery, D. C., Runger, G. C.: Applied Statistics and Probability for Engineers, John Wiley & Sons Inc, 2003, ISBN 978-0471204541
Forms of Teaching
Lecture
Exercise
Consultation
Teaching Methods
Frontal Teaching
Individual Work– Individual or Individualized Activity
Exercise on computers using Excel and the R system
Lectures in Power-Point using hyperlinks
Elaboration of compulsory and voluntary exercises
Student Workload
ActivitiesNumber of Hours of Study Workload
Daily StudyCombined Study
Preparation for the Mid-term Test2424
Preparation for Seminars, Exercises, Tutorial2668
Preparation for the Final Test1515
Elaboration of compulsory and voluntary exercises1313
Attendance on Lectures26 
Attendance on Seminars/Exercises/Tutorial/Excursion2610
Total:130130
Assessment Methods and Assesment Rate
Test – mid-term 15 %
Test – final 70 %
test průbežný 2 nebo domácí cvičení a docházka na přednášky (in Czech) 15 %
Exam conditions
Grading of the course: First Test/Seminar Work/ … : maximum 30% (0-30 points), Final Test: maximum 70% (0-70 points). Successful graduates of the course have to get totally at least 70 points: A: 100 – 98, B: 97,99 – 91, C: 90,99 – 80, D: 79,99 – 73, E: 72,99 – 70, FX: 69,99 – 30, F 29,99 - 0.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught each semester.
The course is also listed under the following terms Summer 2008, Winter 2008, Summer 2009, Winter 2009, Summer 2010, Winter 2010, summer 2011, winter 2011, summer 2012, winter 2012, summer 2013, winter 2013, summer 2014, winter 2014, summer 2015, winter 2015, Summer 2016, summer 2017, winter 2017, summer 2018, winter 2018, summer 2019, winter 2019, summer 2020, winter 2020, summer 2021.
  • Enrolment Statistics (winter 2016, recent)
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