Course syllabus

Statistics, Statistical Theory, Second Cycle, 7.5 credits

Course code: ST421A Credits: 7.5
Main field of study: Statistics Progression: A1F
    Last revised: 12/03/2020
Education cycle: Second cycle Approved by: Head of school
Established: 01/11/2019 Reading list approved: 12/03/2020
Valid from: Autumn semester 2020 Revision: 1

Aims and objectives

General aims for second cycle education

Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall

  • further develop the ability of students to integrate and make autonomous use of their knowledge
  • develop the students' ability to deal with complex phenomena, issues and situations, and
  • develop the students' potential for professional activities that demand considerable autonomy, or for research and development work.

(Higher Education Act, Chapter 1, Section 9)

Course objectives

Knowledge and comprehension

After completing the course the student shall have

  • acquired deeper knowledge of probability theory
  • deeper knowledge of various distributions and their properties as well as properties of a random sample
  • acquired deeper knowledge of statistical theory.

Skills and ability

After completing the course the student shall have

  • the ability to apply statistical theory to practical problems
  • the ability to identify structure and analyse practical problems using probability theory.

Capability of assessment and approach

After completing the course the student shall have the ability to

  • independently seek new knowledge and judge its relevance for the statistical issue at hand.

Main content of the course

  • Basic concepts within probability theory: probability, random variable, distribution, etc.
  • Probability theory: set theory, basics of probability theory, conditional probability and independence, random variables, distribution functions, density and mass functions.
  • Transformations and expectations: distributions of functions of a random variable, expected values, moments and moment generating functions.
  • Common families of distribution: discrete distributions, continuous distributions, exponential families.
  • Multiple random variables: joint and marginal distributions, conditional distributions and independence, bivariate transformations, covariance and correlation, multivariate distributions.
  • Properties of a random sample: basic concepts of a random sample, sums of random variables from a random sample, sampling from the normal distribution, convergence concepts.
  • Basic concepts within statistical theory: test statistic, sufficiency, estimator, etc.
  • Principles of data reduction: the sufficiency principle, the likelihood principle, the equivariance principle.
  • Point estimation: methods of finding estimators, methods of evaluating estimators.
  • Hypothesis testing: methods of finding tests, methods of evaluating tests.
  • Interval estimation: methods of finding interval estimators, methods of evaluating interval estimators.
  • Asymptotic evaluations: point estimation, robustness, hypothesis testing, interval estimation.

Teaching methods

Lectures and math exercises.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Examination methods

Written Examination, 6 credits (Code: A001)
Individual written examination.

Assignments, 1.5 credits (Code: A002)
Four indvidual written assignments.


For students with a documented disability, the university may approve applications for adapted or other forms of examinations.

For further information, see the university's local examination regulations (in Swedish).

Grades

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may prescribe which grading system shall apply. The grade is to be determined by a teacher specifically appointed by the university (an examiner).

In accordance with university regulations regarding grading systems for first and second-cycle courses (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades shall be used: Fail (U), Pass (G) or Pass with Distinction (VG). For courses that are included in an international Master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the grading scale of A-F shall be used. The vice-chancellor, or a person appointed by the vice-chancellor, may decide on exceptions from this provision for a specific course, if there are special grounds.

Grades used on course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Written Examination
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Assignments
Grades used are Fail (U) or Pass (G).

For further information, see the university's local examination regulations (in Swedish).

Comments on grades

To obtain a passing grade for the course as a whole, a passing grade is required on all course components. The final grade for the entire course is a function of the grades of the course components. Detailed information on the requirements for different grade levels is given at the course start.

Specific entry requirements

First-cycle courses of 90 credits in statistics, including an independent project of 15 credits, alternatively 30 credits are for studies in statistics and 60 credits for mathematics, as well as the course Statistics, Mathematics for Statistical and Economic Analysis, second cycle, 7.5 credits, or first-cycle courses of 90 credits in economics, including an independent project of 15 credits as well as courses of 60 credits in statistics and the course Statistics, Mathematics for Statistical and Economic Analysis second cycle, 7.5 credits. The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations (in Swedish).

Transfer of credits for previous studies

Students who have previously completed higher education or other activities are, in accordance with the Higher Education Ordinance, entitled to have these credited towards the current programme, providing that the previous studies or activities meet certain criteria.

For further information, see the university's local credit transfer regulations (in Swedish).

Reading list and other teaching materials

Required Reading

Casella George, Roger L. Berger 2002, 2. ed.
Statistical Inference
Pacific Grove, Calif. : Duxbury, ISBN/ISSN: 0-534-24312-6, 660 pages