Course: Statistics

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Course title Statistics
Course code KKM/STAT
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study 3
Semester Winter
Number of ECTS credits 6
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction unspecified
Work placements unspecified
Recommended optional programme components None
Lecturer(s)
  • Rost Michael, doc. Ing. Ph.D.
  • Zemek František, doc. Mgr. Ing. Ph.D.
  • Bystřický Václav, Ing. Ph.D.
Course content
Lectures: 1) Introduction to the course, requirements, basic terminology; 2) Probability; 3) Random variable; 4) Probability distribution 5) Descriptive statistics; 6) Estimates and Confidence Intervals; 7) Introduction to hypothesis testing; 8) Single-line t-test; 9) Two-choice t-test and pair t-test; 10) One-way ANOVA; 11) Multiple comparison; 12) Nonparametric methods; 13) Regression and correlation analysis; Practices 1) Conditions for passing the subject, installation of Statistica software, basics of sotware Statistica 2) Descriptive statistics - nominal and ordinal variables 3) Descriptive statistics - quantitative variables 4) Writing test 1 5) Combinatorics 6) Probability 7) Writing test 2 8) Estimation of parameters confidence interval 9) Hypothesis testing what is the hypothesis, testing principles, one-sample t-test 10) Hypothesis testing student´s t-test, F-test, two-sample t-test 11) Correlation and regression 12) Hypothesis testing and regression revision 13) Writing test 3 14) One-way ANOVA

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming)
  • Preparation for credit - 60 hours per semester
  • Preparation for exam - 60 hours per semester
  • Class attendance - 56 hours per semester
Learning outcomes
The course introduces the basic procedures for data processing. Introduces students to the probability calculus, deals with system descriptors and basic principles of inductive reasoning.
Students understand basic principles of statistical methods and probability. They are able to perform hypothesis testing and regression analysis.
Prerequisites
knowledge of secondary school mathematics

Assessment methods and criteria
Combined exam, Test

Credit requirements: Active participation in exercises. Exam requirements: To successfully complete the written part of the exam, it is necessary to obtain min. 60% points. It applies to both the computer and theory test. Successful completion of the computer test is a condition for taking the theory test.
Recommended literature
  • Anděl, J. Základy matematické statistiky. Praha : MFF UK, 2005.
  • ČERMÁKOVÁ, A. Statistika II. JU v Českých Budějovicích, 2005.
  • DRAPER, N., SMITH, H. Applied Regression analysis, Wiley and Sons. New York, 1981.
  • HENDL, JAN. Přehled statistických metod zpracování dat : analýza a metaanalýza dat. Praha, Portál, 2004.
  • ZVÁRA, K. Biostatistika. Praha : Karolinum, 1998. ISBN 80-7184-773-9.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Agriculture and Technology Study plan (Version): Agribussines (2014) Category: Agriculture and forestry 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Agriculture and Technology Study plan (Version): Land Adjustment and Real Estate Trade (2017) Category: Agriculture and forestry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Agriculture and Technology Study plan (Version): Agricultural Ecology (2017) Category: Agriculture and forestry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Agriculture and Technology Study plan (Version): Agricultural Biotechnology (2014) Category: Agriculture and forestry 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Agriculture and Technology Study plan (Version): Agriculture Engineering (2014) Category: Agriculture and forestry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Agriculture and Technology Study plan (Version): Agricultural Biotechnology (2014) Category: Agriculture and forestry 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Agriculture and Technology Study plan (Version): Agricultural Ecology (2017) Category: Agriculture and forestry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Agriculture and Technology Study plan (Version): Agriculture Engineering (2014) Category: Agriculture and forestry 1 Recommended year of study:1, Recommended semester: Winter