6 ECTS credits
180 h study time

Offer 1 with catalog number 1021094BER for all students in the 1st semester at a (B) Bachelor - advanced level.

Semester
1st semester
Enrollment based on exam contract
Possible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Enrollment Requirements
Students who want to enroll for this course, must have passed for 'Statistics for the Social Sciences' and must have obtained at least 30 ECTS-credits on bachelor level
Taught in
English
Partnership Agreement
Under interuniversity agreement for degree program
Faculty
Faculty of Social Sciences & SolvayBusinessSchool
Department
Sociology
External partners
Universiteit Gent
Educational team
Amelie Van Pottelberge (course titular)
Activities and contact hours
39 contact hours Lecture
39 contact hours Seminar, Exercises or Practicals
102 contact hours Independent or External Form of Study
Course Content

This course has two main objectives. First, it gives  an introduction to the analysis of variance (one-way ANOVA) and the multiple linear regression model. Building further on the knowledge and insights acquired in the educational component ‘Statistics for the Social Sciences’ (1BA), the course addresses the basics of inferential statistics, statistical control and multivariate analysis. More specifically, we will see the following techniques: t-test for the difference between two means, ANOVA, bivariate regression (basics, residuals and influence statistics, inferential statistics), multiple regression (basics, redundancy/suppression, inferential statistics and assumptions, categorical independent variables, F-tests, and interaction effects).

The second objective concerns the analysis of large and complex datasets in a correct and sound manner. Students learn the basic techniques for data transformations and statistical analyses in the statistical analysis software package SPSS, both by way of the menu interface and syntax commands, under supervision of an assistant. To this purpose, we will use real datasets, taking research questions embedded in social scientific theory as our point of departure.

The aimed competences of this course are threefold. First, it aims to learn students to choose the appropriate statistical technique for specific research questions. Second, students are learned to carry out the chosen technique adequately. Third, students are learned to interpret the results of their analyses aptly. In the coming years, students can build further on the knowledge, insights and skills they have acquired here, in view of learning more advanced statistical techniques and models.

Additional info

Didactic forms

  • Lectures and interactive lectures with class discussions, peer-to-peer learning, and triple-jump interactive techniques
  • E-learning
  • Guided PC exercises

Course material

Reader: Mclendon, M.J. (1998). Multiple regression and causal analysis. Itasca, Ill.: Peacock Publishers (selected chapters)

    + other chapters to be communicated at the start of this course

    + slides of theoretical lectures and practice sessions

Learning Outcomes

General competences

For the covered statistical techniques, the course expects students upon completion:

  • to have insight into the possibilities and limitations of quantitative techniques of analysis for social sciences research;
  • to understand published statistical analyses, to be able to correctly interpret, and critically evaluate, them;
  • to be able to make a sound choice from different statistical techniques to answer a research question in a scientifically sound manner;
  • to be able to correctly calculate and interpret statistical measures;
  • to understand the advantages and limitations of the different statistical measures;
  • to be able to independently translate a research question in a statistical model;
  • to be able to analyze a statistical model in SPSS;
  • to be able to independently carry out the necessary data transformations in SPSS;
  • to have become a critical and legitimate user of statistics (life-long learning)
  • to be able to adjust the personal learning process.

More generally, the course addresses the following program learning objectives:

  • LO5: knows and can explain the multilayered and complex character of social, political and media-related facts and phenomena.  
  • L07: knows the methods of data selection, management and analysis that prevail within the domains of the social sciences.
  • LO8: can interpret and analyse contemporary social phenomena and problems and can take position, relying on contemporary theories in the domain of the social sciences, in debates on them. 
  • LO13: can, with limited supervision, formulate a valid scientific research question on a social sciences research topic.  
  • LO14: can, with limited supervision, set up a scientific and methodologically correct research design to answer a research question in the domain of the social sciences.  
  • LO15: can, with limited supervision, perform the necessary methodological steps (data selection, processing and management, and analysis) to answer a research question on a social sciences research topic. 
  • LO16: can report, independently, on their research in both oral and written form.  
  • LO18: can reflect on and evaluate their learning process and research and can deal with criticism in a constructive manner.  

 

Grading

The final grade is composed based on the following categories:
Written Exam determines 100% of the final mark.

Within the Written Exam category, the following assignments need to be completed:

  • Written Exam with a relative weight of 1 which comprises 100% of the final mark.

Additional info regarding evaluation

Formative assessment

  • Interactive lectures with group discussion, peer-to-peer learning, and application of theoretical subject matter to everyday examples;
  • Practical exercise sessions under supervision of an assistant. By preparing and revising exercises, students can monitor their progress with the subject matter. The exercises will be accompanied by feedback. Synthesis exercises appear twice throughout the year, which give students a good insight into their mastery of the subject matter.

Summative assessment

The written exam is composed of two parts. The first part is paper-and-pencil, and involves both theoretical and practical questions. For the second part, students will solve practical questions with the help of computer software, including SPSS. This exam targets insight in rather than reproduction of the subject matter. Both parts count for 50% of the total grade, which is calculated by summing both partial scores. It is not possible to pass one part if the total score of the exam is below 50%.

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Bachelor of Social Sciences: Communication Studies
Bachelor of Social Sciences: Political Sciences
Bachelor of Social Sciences: Sociology
Bachelor of Social Sciences: Startplan