Course: Applied Statistics 1

« Back
Course title Applied Statistics 1
Course code MUSKM/3AST1
Organizational form of instruction Lecture
Level of course unspecified
Year of study not specified
Semester Summer
Number of ECTS credits 5
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Urbánek Tomáš, Ing. Ph.D.
Course content
- Introduction to the course, fundamental principles of combinatorics - Fundamentals of probability theory and operations with events - Conditional probability and independence of events - Introduction to random variables and their general properties - Discrete random variables and selected probability distributions - Continuous random variables and probability density - Characteristics of random variables, expected value and variance - Fundamentals of descriptive statistics and exploratory data analysis - Relationship between population and sample, principles of statistical surveying - Estimation theory and point estimates of parameters - Method of moments (MoM) for estimating distribution parameters - Advanced topics in applied statistics and course summary

Learning activities and teaching methods
Lecturing
  • Preparation for examination - 40 hours per semester
  • Home preparation for classes - 65 hours per semester
  • Preparation for course credit - 20 hours per semester
prerequisite
Knowledge
Fundamental knowledge of high school mathematics, summation principles, and basic differential and integral calculus of functions of one variable.
Fundamental knowledge of high school mathematics, summation principles, and basic differential and integral calculus of functions of one variable.
Skills
Ability to perform basic algebraic operations, work with sets, and calculate simple derivatives and integrals of functions.
Ability to perform basic algebraic operations, work with sets, and calculate simple derivatives and integrals of functions.
learning outcomes
Knowledge
define basic concepts of combinatorics and the axiomatic definition of probability
define basic concepts of combinatorics and the axiomatic definition of probability
describe the characteristics of discrete and continuous random variables and their distributions
describe the characteristics of discrete and continuous random variables and their distributions
explain the principles of descriptive statistics and the difference between a population and a sample
explain the principles of descriptive statistics and the difference between a population and a sample
clarify the essence of point estimates and the method of moments (MoM)
clarify the essence of point estimates and the method of moments (MoM)
Skills
Calculate the probability of compound events using combinatorial rules
Calculate the probability of compound events using combinatorial rules
determine numerical characteristics of random variables, such as expected value and variance
determine numerical characteristics of random variables, such as expected value and variance
process a data set using descriptive statistics methods and interpret the obtained results
process a data set using descriptive statistics methods and interpret the obtained results
apply point estimates of distribution parameters to data sets
apply point estimates of distribution parameters to data sets
teaching methods
Knowledge
Lecturing
Lecturing
Practice exercises
Practice exercises
Skills
Practice exercises
Practice exercises
Lecturing
Lecturing
assessment methods
Knowledge
Analysis of the student's performance
Analysis of the student's performance
Grade (Using a grade system)
Grade (Using a grade system)
Recommended literature
  • NEUBAUER, J., SEDLAČÍK, M., KŘÍŽ, O. Základy statistiky. Aplikace v technických a ekonomických oborech. 2. roz. vyd.. Praha: Grada, 2016. ISBN 978-80-247-5786-5.
  • ROSS, Sheldon M. a Erol A. PEKÖZ. A second course in probability. Second edition. Cambridge, United Kingdom. 2023.
  • ROSS, Sheldon M. Introduction to probability models. 13th ed. Burlington, Mass. 2023.
  • URDAN, Timothy C. Statistics in plain English. Fifth edition. New York. 2022.
  • ZVÁRA, K., ŠTĚPÁN, J. Pravděpodobnost a matematická statistika. 6. vyd.. Praha: Matfyzpress, 2019. ISBN 978-80-7378-388-.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester