VŠTE:STA Statistics - Course Information

STA Statistics

Extent and Intensity

2/2. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

RNDr. Tomáš Ditrich, Ph.D. (lecturer)
doc. RNDr. Jaroslav Stuchlý, CSc. (lecturer)
Ing. Petra Bednářová, Ph.D. (assistant)

Guaranteed by

doc. RNDr. Jaroslav Stuchlý, CSc.
Department of Civil Engineering – Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice

Timetable of Seminar Groups

STA/K0: Sun 6. 3. 8:15–9:45 B4, 9:55–11:25 B4, Sun 1. 5. 8:15–9:45 A4, 9:55–11:25 A4, Sat 14. 5. 8:15–9:45 A4, T. Ditrich
STA/01: Tue 13:50–15:20 A4, J. Stuchlý
STA/02: Tue 9:55–11:25 D315, J. Stuchlý
STA/03: Tue 12:10–13:40 D215, J. Stuchlý

Prerequisites (in Czech)

INF_2 Informatics II || IPE_II Informatics for Economists 2

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 50 student(s).
Current registration and enrolment status: enrolled: 0/50, only registered: 0/50

fields of study / plans the course is directly associated with

• Business Administration and Management (programme VŠTE, EM)

Course objectives supported by learning outcomes

To teach students to collect, collate, process and present statistical data. To acquaint them with the basic procedures from the area of statistical induction, methods of analysis of qualitative and quantitative characters and elements time series analysis. Focusing particularly on the economic interpretation of the result.

Syllabus

• 1 Methods of descriptive statistics (basic statistical concepts, statistical investigation stages, frequency allocation 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, characteristics of aggregate data, simple and composite indices, price indices) 3 Probability and probability distributions and their numerical characteristics (random events and their probabilities, properties of probability, conditional independent and random events and their probabilities, and comprising the aggregate probability of a random variable and its probability distribution, mean and variance of random variables) 4 Basic probability models (binomial distribution, Poisson and normal, their mean and variance, standard random variable, the standard normal distribution tables, the distribution and quantile functions and their tables) 5 Survey sampling, sample distribution characteristics and foundations of statistical induction (basic and sample, importance and types of sample surveys, sampling distributions, central limit theorem, the distribution characteristics of the sample, sample distribution and average rate) 6 Point and interval estimates (basic concepts, point and interval estimates of population mean and proportion, and variance, determining the extent of the file) 7 Testing hypotheses (null and alternative hypothesis, significance level test and its determination, identification of the refusal, the critical value of the test, test test, the choice between two hypotheses, test hypotheses about the diameter of  , and variance ratio, p-value test) 8 Further statistical tests (test hypotheses on   line two averages and variances   two stakes, testing in small samples!) 9 Dependencies statistics ( testing independence in contingency table, Single-factor analysis of variance, depending on power level) 10 Simple linear regression and correlation (causal and nekauzální dependence, covariance and correlation, scatter diagram, the method of least squares regression line, correlation coefficient, other types of regression functions) 11 Extending a simple linear regression (population and sample regression function estimates of regression parameters and their properties, standard error of regression parameters and their confidence intervals, tests in regression analysis!) 12 Multivariate regression and prognostic applications Regression (multivariate regression model, the partial regression coefficients and their interpretation, the coefficient of determination, tests of significance   model, using regression to predict!) 13 Introduction to time series analysis (time series and its graph, at some point and interval time series characteristics of a time series, leveling the time series moving average) 14 Revision. Reserve time.

Literature

required literature
• 2. Marek L., Jarošová E., Pecáková I., Pourová Z., Vrabec M. (2005): Statistika pro ekonomy – aplikace, Professional Publishing, Praha. ISBN 80-86419-68-1
• 1. Hindls,R. a kol.: Statistika pro ekonomy. Praha, Professional Publishing 2006, ISBN 80-86946-16-9

recommended literature
• 8. Jarošová,E-Pecáková,I.: Příklady k předmětu statistika B. Skripta VŠE, Praha 2000. ISBN 80-245-0015-9
• 4. Stuchlý,J.: Statistika I. Skripta FM VŠE Praha 1999. ISBN 80-7079-754-1 (i v elektronické podobě)
• 3. Wisniewski,M.: Metody manažerského rozhodování. Grada Publishing 1996, kap. 3, 4, 5, 7, 9, 10. ISBN 80-7169-089-9
• 5. Stuchlý,J.: Statistika II. Skripta FM VŠE Praha 1999. ISBN 80-7079-035-0 (i v elektronické podobě)
• 7. Arltová,M.-Bílková,D.-Jarošová,E.-Pourová,Z.: Příklady k předmětu Statistika A. Skripta VŠE, Praha 2001. ISBN 80-245-0178-3
• 6. Seger,J.-Hindls,R.: Statistické metody v tržním hospodářství Vicoria Publishing Praha 1995. ISBN 80-7187-058-7

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

Student Workload

Activities	Number of Hours of Study Workload
	Daily Study	Combined Study
Preparation for the Mid-term Test	24	24
Preparation for Seminars, Exercises, Tutorial	26	68
Preparation for the Final Test	15	15
Elaboration of compulsory and voluntary exercises	13	13
Attendance on Lectures	26
Attendance on Seminars/Exercises/Tutorial/Excursion	26	10
Total:	130	130

Assessment Methods and Assesment Rate

Test – mid-term 15 %
Test – final 50 %
activity at seminars 5 %
a midterm test 2 15 %
a midterm test 3 15 %

Exam conditions

For admission to the exam, the student has to gain at least 18 points from the total of 30 points of three tests. It is possible to evaluate the activity at seminars and the quality of elaborated individual exercises by 0-3 extra points. The students can write the reparative test during the exam period to get the admission to the exam (partial test - 10 points of final test - 30 points). The exam will be assessed on the basis of the computer test using IS (testing theoretical and application part) - 20 points. The evaluation will be done using the following table. A: 18,1 – 20 bodů, B: 16,1 - 18 points, C: 14,1 – 16 points, D: 12,1 – 14 points, E: 10,1 – 12 points, Fx: 5,1 – 10 points, F: 0 – 5 points

Language of instruction

Czech

Further Comments

The course is taught each semester.

• Enrolment Statistics (summer 2011, recent)
  
• Permalink: https://is.vstecb.cz/course/vste/summer2011/STA