MAS01 Applied statistics I

Faculty of Science
autumn 2021
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
Wed 14:00–15:50 M1,01017
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
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 2020, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (autumn 2021, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2021/MAS01