Syllabus

Mathematics for microdata analysis

Code
ST2004
Points
7.5 ECTS-credits
Level
First Cycle Level 2
School
School of Information and Engineering
Subject field
Statistics (STA)
Group of Subjects
Statistics
Disciplinary Domain
Natural Science, 100%
This course can be included in the following main field(s) of study
Microdata Analysis1
Progression indicator within (each) main field of study
1G1F
Approved
Approved by the Faculty School of Information and Engineering, 07 September 2010.
This syllabus is valid from 21 September 2010.
Revised
Revised, 18 December 2012.
Revision is valid from 31 December 2012.
Discontinued
22 December 2021

Learning Outcomes

On completion of this course the student will be able to:
- Apply set theory in a probability theoretic context
- Differentiation
- Apply the limit concept
- Perform Taylor‘s expansion
- Execute matrix operations
- Calculate Riemann integrals


The student will acquire knowledge of:
- The theory behind the Riemann Integral
- Sequences of sets/events and series of functions
- Eigenvalues

Course Content

The course includes mathematics that provide preparation for further studies in statistics and microdata analysis.
The course covers the following topics: set theory, supremum and infimum, limits and
continuity, differentiation, convex and inverse functions, the mean value theorem,
Taylor‘s formula, maxima and minima, sequences and series, The Riemann integral,
improper Riemann integrals, continuity and derivatives of functions in several
dimensions, The Riemann integral of a functions in several dimensions.

Assessment

Written examination.

Forms of Study

Web based lectures and tutorials

Grades

The Swedish grades U–VG.

Prerequisites

  • At least a total of 30 credits in one or several of this subjects; statistics, mathematics, computer science

Other Information

The student is entitled to four resits