EXC 2904 Statistics

EXC 2904 Statistics

Course code: 
EXC 2904
Course coordinator: 
Svein Lund
Course name in Norwegian: 
Product category: 
Bachelor - Common Courses
2018 Spring
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

This course gives an introduction to statistics. Main themes are descriptive statistics, probability and hypothesis testing. Formulas and formal procedures play an important role, but the emphasis is on developing statistical literacy and critical thinking.

Learning outcomes - Knowledge
  • To understand the relevance of statistical analysis in economics and marketing
  • Knowledge of basic concepts and overview of statistics
  • Understanding the difference between a population and a sample
  • Understanding what a random variable and a statistical model is
  • Understanding that statistical methods are based on assumptions that must be checked
  • Understanding what estimation and hypothesis testing is about
  • To be able to reflect on the role of randomness
  • To be acquainted with the statistical and mathematical notations used in statistics
Learning outcomes - Skills
  • To be able to discern randomness from real underlying effects
  • To be able to use statistical software and interpret computer displays from such software
  • To be able to produce statistical graphics
  • To be able to compute probabilities and confidence intervals
  • To be able to conduct the most basic types of hypothesis testing and estimation
Learning Outcome - Reflection
  • To understand that statistical methods can be wrongly applied and lead to false conclusions
  • To understand that in many situations a statistical analysis will help making better decisions
Course content
  • Graphical and descriptive statistics
  • Random samples and populations
  • Discrete and continuous random variables
  • Probability
  • Statistical models
  • Estimation
  • Confidence intervals
  • Hypothesis testing
  • Correlation and regression
  • Chi square tests
Learning process and requirements to students

There are 48 course hours, 38 of which are ordinary lectures where the syllabus is covered. The remaining 10 hours will be dedicated to SAS JMP or Excel demonstrations in class.  

For each week there will be given a work programme with literature references and exercises. Training / use of Excel will be integrated into teaching. In the lectures the theory will be exemplified by a set of SAS JMP data samples with exercises. The final exam is loosely based on these SAS JMP examples.

The course uses an appropriate statistical software.

Work requirements
There are 8 mandatory multiple choice tests to be answered in It's Learning. 

If a test is not approved in the first try, the student can retry. It is mandatory that the student get approved at least 5 of these tests in order to take the final exam.

Software tools
Additional information

Re-sit examination
Students that have not gotten approved the coursework requirements, must re-take the exercises during the next scheduled course.

Students that have not passed the written examination or who wish to improve their grade may re-take the examination in connection with the next scheduled examination.


Higher Education Entrance Qualification.

Required prerequisite knowledge

No particular prerequisites.

Mandatory courseworkCourseworks givenCourseworks requiredComment coursework
Mandatory85It is mandatory that the student must get approved at least 5 of 8 tests in order to take the final exam.
Mandatory coursework:
Mandatory coursework:Mandatory
Courseworks given:8
Courseworks required:5
Comment coursework:It is mandatory that the student must get approved at least 5 of 8 tests in order to take the final exam.
Exam category: 
Form of assessment: 
Written submission
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
5 Hour(s)
Exam code: 
Grading scale: 
Examination when next scheduled course
Exam organisation: 
Ordinary examination
Total weight: 
Student workload
48 Hour(s)
50 Hour(s)
Multiple-choice tests on Itslearning.
Group work / Assignments
42 Hour(s)
SPSS work
Student's own work with learning resources
40 Hour(s)
20 Hour(s)
Exam incl. preparations.
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.