OPF:INMBASTA Statistics - Course Information

INMBASTA Statistics

Extent and Intensity

2/1/0. 6 credit(s). Type of Completion: zk (examination).

Teacher(s)

Mgr. Radmila Krkošková, Ph.D. (lecturer)

Guaranteed by

doc. RNDr. David Bartl, Ph.D.
Contact Person: Mgr. Radmila Krkošková, Ph.D.

Timetable

Mon 11:25–13:00 A423

• Timetable of Seminar Groups:

INMBASTA/01: Mon 13:05–13:50 A423, R. Krkošková

Prerequisites (in Czech)

FAKULTA(OPF) && TYP_STUDIA(B) && FORMA(P)

Course Enrolment Limitations

The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 2/20, only registered: 2/20

fields of study / plans the course is directly associated with

• Economics and Management (programme OPF, B_EME)

Course objectives

Following up on the knowledge from the core subjects Quantitative Methods and Informatics, the course aims to explain the basic concepts and findings of mathematical and economic statistics, as well as fundamental statistical methods, with a focus on applications in the economic field. The goal is also to acquire relevant computational skills and the ability to solve statistical problems using statistical functions in Excel on a PC.

Learning outcomes

After completing the course, the student will:
- have knowledge of the basic concepts and findings of mathematical and economic statistics;
- have knowledge of fundamental statistical methods;
- be able to apply the basic concepts and findings of mathematical and economic statistics, as well as fundamental statistical methods, particularly the economic field;
- acquire relevant computational skills and the ability to solve statistical problems using statistical functions in Excel on a PC.

Syllabus

• 1. Introduction: statistics and the significance of statistics
  When the statistics are not reliable. Statistical methods in marketing, business and entrepreneurship. Applications of statistical methods: descriptive statistics, statistical induction, statistical decision making and inference.
• 2. Descriptive statistics: categorical and numerical data
  Categorical (qualitative) data. Frequency distribution. Numerical (qualitative) data. Frequency distribution, statistical location (arithmetic mean, median, mode), statistical variability or dispersion (variance and standard deviation), shape of the distribution (skewness, kurtosis).
• 3. Probability and random variables
  Intuitive definition of the probability and fundamental concepts. Combinatorics. Bernoulli trials. Probability as the relative frequency. Probability properties. Discrete and continuous random variable. The probability distribution of a random variable and its characteristics (expected value, variance and standard deviation, mode).
• 4. Probability models (discrete and continuous)
  Discrete probability models, discrete random variables, their characteristics and charts: uniform distribution, binomial distribution, Poisson distribution. Continuous probability models, continuous random variables, their characteristics and charts: uniform distribution, Gauss normal distribution, exponential distribution, Student's t-distribution. Probability cumulative distribution function and the quantile function. Probability density function. Central limit theorem.
• 5. Point and interval estimation
  Sample data, point estimates, properties of point estimates. Interval estimates, confidence interval for the mean value.
  6. Statistical hypothesis testing and analysis of variance.
  Parametric statistical tests. Statistical hypothesis, null hypothesis (H0), alternative hypothesis (H1). Hypothesis testing for a mean. Single-sided tests. Two-sided tests. Non-parametric statistical tests. The chi-squared distribution. Pearson's chi-squared test. Statistical tests of independence in 2x2 contingency table. Analysis of variance (ANOVA), single factor or one-way ANOVA, coefficient of determination and correlation ratio.
• 7. Linear regression and regression analysis
  Stochastic dependence. Simple linear regression. Multiple linear regression. Other linear models. The choice of the regression function, regression parameters estimation, coefficient of determination and correlation ratio, linearized regression functions.

Literature

required literature
• SIEGEL, Andrew F. and Michael R. WAGNER. Practical Business Statistics. Eighth Edition. Academic Press (Elsevier), 2022. ISBN 978-0-12-820025-4. Available from: https://dx.doi.org/10.1016/C2019-0-00330-5. info
• KELLER, Gerald and Nicoleta GACIU. Statistics for Management and Economics. 2nd Edition. Cengage, 2019. ISBN 978-1-4737-6826-0. info

recommended literature
• HERKENHOFF, Linda and John FOGLI. Applied Statistics for Business and Management using Microsoft Excel. Second Edition. Springer, 2025. ISBN 978-3-031-46370-9. Available from: https://dx.doi.org/10.1007/...-.-...-.....-. info
• BRASE, Charles Henry, Corrinne Pellillo BRASE, Jason Mark DOLOR and James Allen SEIBERT. Understandable Statistics: Concepts and Methods. 13th Edition. Cengage, 2022. ISBN 978-0-357-71917-6. info
• THRANE, Christer. Applied Regression Analysis: Doing, Interpreting and Reporting. 1st Edition. Routledge, 2020, 202 pp. ISBN 978-1-138-33547-9. info
• ANDERSON, David, Dennis J. SWEENEY, Thomas WILLIAMS, Jeffrey D. CAMM, James J. COCHRAN, Michael J. FRY and Jeffrey W. OHLMANN. Essentials of Modern Business Statistics with Microsoft® Excel®. 8th Edition. Cengage, 2020. ISBN 978-0-357-56952-8. info
• QUIRK, Thomas J. Excel 2019 for Business Statistics: A Guide to Solving Practical Problems. Second Edition. Springer, 2020. ISBN 978-3-030-39260-4. Available from: https://dx.doi.org/10.1007/978-3-030-39261-1. info
• ANDERSON, David, Dennis J. SWEENEY, Thomas A. WILLIAMS, Jeffrey D. CAMM, James J. COCHRAN, James FREEMAN and Eddie SHOESMITH. Statistics for Business and Economics. 5th Edition. Cengage, 2020. ISBN 978-1-4737-6845-1. info
• UBØE, Jan. Introductory Statistics for Business and Economics: Theory, Exercises and Solutions. Springer, 2017. ISBN 978-3-319-70935-2. Available from: https://dx.doi.org/10.1007/978-3-319-70936-9. info
• ÖZDEMIR, Durmuş. Applied Statistics for Economics and Business. Second Edition. Springer, 2016. ISBN 978-3-319-26495-0. Available from: https://dx.doi.org/10.1007/978-3-319-26497-4. info
• WONNACOT, T. H. and J. W. WONNACOT. Introductory statistics for business and economics. New York: Wiley and Sons, 1990. ISBN 0-4716-1517-X. info

Teaching methods

lectures and seminars (exercises, problems, examples and case studies)

Assessment methods

Requirements for the student: regular study, attendance at seminars: min. 70 %, or independent solution of a statistical problem, or independent preparation of a seminar paper.
Assessment: two written tests.
Assessment methods: midterm test (worth 30 points), final exam test (worth 70 points); extra points for tasks and homework.
Grading:
• 90 – 100 points — A
• 80 –  89 points — B
• 70 –  79 points — C
• 65 –  69 points — D
• 60 –  64 points — E
•  0 –  59 points — F

Language of instruction

English

Further Comments

Study Materials

• Enrolment Statistics (recent)
  
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