Syllabus for Inference

Inferens

A revised version of the syllabus is available.

Syllabus

  • 7.5 credits
  • Course code: 2ST120
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Statistics A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (G), Pass with distinction (VG)
  • Established: 2013-03-26
  • Established by:
  • Revised: 2020-03-27
  • Revised by: The Department Board
  • Applies from: Spring 2020
  • Entry requirements:

    120 credits including 90 credits in statistics.

  • Responsible department: Department of Statistics

Learning outcomes

After completing the course the student is expected to

  • be familiar with and understand the basic principles of estimation
  • be familiar with and understand the basic principles of testing
  • be familiar with and understand the basic principles of confidence intervals.

Content

Method of moments, method of maximum likelihood, the invariance principle, consistency and unbiasedness, likelihood ratio tests, LM (score) and Wald tests, significance level and power function, properties of tests, interval estimation.

Instruction

Instruction is given in form of lectures.

Assessment

The examination takes place partly through a written examination at the end of the course and/or through presentation orally and in written form of compulsory assignments.

"If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator."

Syllabus Revisions

Reading list

Reading list

Applies from: Spring 2020

Some titles may be available electronically through the University library.

  • Casella, George; Berger, Roger L. Statistical inference

    2. ed.: Pacific Grove, CA: Duxbury, 2008

    Find in the library

    Mandatory

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