Mathematics BA (A), Statistics with Probability, 7.5 Credits
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• June 1 for a course that starts in the autumn semester
• November 15 for a course that starts in the spring semester
• April 1 for a course that starts in the summer
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Syllabus:
Matematik GR (A), Statistik med sannolikhetslära, 7,5 hp
Mathematics BA (A), Statistics with Probability, 7.5 Credits
General data
- Code:MA137G
- Subject/Main field:Mathematics
- Cycle:First cycle
- Progression:(A)
- Credits:7,5
- Progressive specialization:G1N - First cycle, has only upper-secondary level entry requirements
- Education area:Naturvetenskap 100%
- Answerable faculty:Faculty of Science, Technology and Media
- Answerable department:Engineering, Mathematics, and Science Education
- Approved:2014-10-13
- Date of change:2023-11-06
- Version valid from:2024-01-02
Aim
The aim of the course is for the student to gain knowledge and appreciation of the benefits gained by the use of statistics in the natural sciences and to enable students to describe and present collected, and interpret the results of using statistical software on data. The main outcome of the course is to provide the student with an understanding of statistical concepts and knowledge of how statistical tools can be used in their own research.
Course objectives
After completing the course, the student should be able to:
- define and calculate basic measures of location and spread
- define concepts and apply basic probability estimates for both discrete and continuous random variables
- explain the background of and compute point estimates and interval estimates
- identify situations where the use of linear regression is suitable
- distinguish between and choose suitable statistical sampling methods
- categorise, compare and calculate z-tests, t- tests, chi-squared tests and ANOVA tests
- use and summarise results from using statistical software.
Content
Descriptive statistics, including linear regression and basic probability theory. Point estimate and confidence interval for the population mean. Statistical sampling methods and hypothesis testing with z-test, t-test, chi-squared test and ANOVA test. An overview of parameter-free tests. The use of statistical packages such as Minitab or R is integrated in the course.
Entry requirements
Selection rules and procedures
The selection process is in accordance with the Higher Education Ordinance and the local order of admission.
Teaching form
Teacher-led theoretical lectures and practical workshops.
Examination form
I100: Assignments, 7.5 Credits
Grade scale: Seven-grade scale, A, B, C, D, E, Fx and F. Fx and F represent fail levels.
Grading criteria for the subject can be found at www.miun.se/gradingcriteria.
The examiner has the right to offer alternative examination arrangements to students who have been granted the right to special support by Mid Sweden University’s disabilities adviser.
Examination restrictions
Students are entitled to three examination opportunities within one year according to the examination format given in this version of the course syllabus. After the one-year period, the examination format given in the most recent version of the course syllabus applies.
Grading system
Seven-grade scale, A, B, C, D, E, Fx and F. Fx and F represent fail levels.
Course reading
Required literature
- Author: Nicholas J. Gotelli, Aaron M. Ellison
- Title: A Primer of Ecological Statistics
- Edition: 2
- Publisher: Oxford University Press
Reference literature
- Author: Svante Körner, Lars Wahlgren
- Title: Statistisk dataanalys
- Edition: 5
- Publisher: Studentlitteratur