MAS01 Applied statistics I

Faculty of Science
Autumn 2020
Extent and Intensity
2/0/0. 2 credit(s) (plus 2 credits for an exam). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
RNDr. Marie Budíková, Dr. (lecturer)
Guaranteed by
doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science
Timetable
Mon 8:00–9:50 prace doma
Prerequisites (in Czech)
NOW( MAS01c Applied statistics I - exer. ) || NOW( MAS10c Applied statistics I - exerc. )
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 199 fields of study the course is directly associated with, display
Course objectives
The aim of the course is:
to teach students to correctly understand important statistical concepts;
to acquaint students with simple statistical methods;
show the student how to interpret outputs from statistical software.
Learning outcomes
Upon completing this course, students will be able to:
understand basic notation of mathematical statistics;
analyze data;
check assumptions about data;
interpret results of statistical processing.
Syllabus
  • Exploratory analysis of data, diagnostics graphs.
  • Random variables, probability distributions, numerical characteristics.
  • Basic notions of mathematical statistics.
  • Testing of normality.
  • Parametrics and nonparametrics tests for one random sample and for two and more independent random samples.
  • Contingency tables.
  • Correlation analysis.
Literature
  • BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ. Průvodce základními statistickými metodami (Guide to basic statistical methods). vydání první. Praha: Grada Publishing, a.s., 2010, 272 pp. edice Expert. ISBN 978-80-247-3243-5. URL info
  • MELOUN, Milan and Jiří MILITKÝ. Počítačová analýza vícerozměrných dat v příkladech. Praha: Academia, 2005. ISBN 80-200-1335-0. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Tomáš LERCH. Základní statistické metody. Vydání první. Brno: Masarykova univerzita, 2005, 180 pp. ISBN 80-210-3886. info
  • HENDL, Jan. Přehled statistických metod zpracování dat :analýza a metaanalýza dat. Vyd. 1. Praha: Portál, 2004, 583 s. ISBN 8071788201. info
Teaching methods
The weekly class schedule consists of 2 hour of lecture.
Assessment methods
The examination is partly written (possibly in the form of a ROPOT) and partly oral. In the oral part, student presents his own statistical data analysis project. Colloquium has presentation part only, while credit is only written (possibly in the form of a ROPOT).
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Předmět by si neměli zapisovat studenti matematických studijních oborů.
Listed among pre-requisites of other courses
Teacher's information
In this semester, teaching will take place remotely. Videos with lectures in the form of annotated slides will be placed in the Teaching Materials. During the time reserved for teaching in the schedule, consultations will take place via MS Teams.
The course is also listed under the following terms Autumn 2010 - only for the accreditation, Spring 2008, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2011 - acreditation, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2020, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2020/MAS01