Basic Statistics

Course content

The objective of the course is to continue to introduce students to quantitative methods and basic statistics. The course builds on the knowledge and skills acquired in Basic Methodology of Social Sciences.

Education

Compulsory course on the 2nd semester BSc in sociology

In Spring 2022 this course will be tought in English.

Learning outcome

Knowledge

The course introduces students to:

  • elementary sampling theory
     
  • basic probability calculus
     
  • discrete and continuous variables
     
  • frequency tables and cross-reference tables
     
  • statistical moments such as mean and variance
     
  • statistical test theory, e.g. in the form of hypothesis testing through t-tests and chi^ 2-tests,
     
  • basic statistical measurements of relations such as correlations and
     
  • statistical controls in cross-reference tables.
     

Students learn to account for these topics. They learn to explain the logic behind the use of statistical moments, statistical test theory and statistical control in cross-reference tables in social science research. They also learn to reflect on the potential and limitations of statistical generalisation, statistical control and the use of statistical moments and measurements of relations.


Skills

The course gives students the opportunity to master basic statistical calculations and tests using standard software such as Excel and Stata. Students learn to:
 

  • formulate, implement and justify the choice of statistical hypothesis tests, e.g. for mean values and cross-reference tables
     
  • calculate and use statistical moments such as mean and variance
     
  • read and report on frequency tables and cross-reference tables
     
  • calculate and apply basic measurements of relations such as correlations and chi^ 2-tests
     
  • use statistical controls in cross-reference tables by checking the relation between two variables for a third variable,
     
  • present and convey the results of statistical analyses of a given problem
     
  • evaluate critically their empirical results in relation to a given problem in a way that demonstrates an understanding of quantitative data and methodology, including its potential and limitations.

     

Competencies

The course provides students with competencies to:
 

  • acquire advanced quantitative methods such as regression analysis
     
  • convert their knowledge and skills in quantitative analyses in research and as consultants by, for example, being able to plan and draw up reports or studies involving regression analysis.
     

Lectures and Exercises

Will be announced in Absalon

Continuous feedback during the course of the semester
ECTS
7,5 ECTS
Type of assessment
Portfolio, -
Individual.
A portfolio assignment is defined as a series of short assignments during the course  that address one or more set questions and feedback is offered during the course. All of the assignments are submitted together for assessment at the end of the course. The portfolio assignments must be no longer than 10 pages in total.
Further details for this exam form can be found in the Curriculum and in the General Guide to Examinations at KUnet.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assessment

Please see the learning outcome

  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 125
  • Exercises
  • 28
  • Exam
  • 25
  • English
  • 206