Quantitative Methods
Course offered :
- Current semester
- Next semester
Course offered by
| Number of credits | 4 |
| Course offered (semester) | Autumn and spring |
| Schedule | Schedule |
| Reading list | Reading list |
Language of Instruction
English.
Pre-requirements
Due to the limited number of spaces available and special entry requirements, admission to the course is limited.
Learning Outcomes
The course gives an introduction to quantitative research methods and statistics. The students will get an understanding of the stages of a quantitative research project. The focus of the course is on the basics of descriptive and inferential statistics. The students will learn various techniques that are used in describing, handling, aggregating, and analyzing quantitative data. They will also get a command of the principles and procedures of making statistical inferences. The students will get hands-on experience in data analysis. In addition, they will be actively involved in a research project, providing them with experience in planning and conducting quantitative research.
Contents
- descriptive statistics (measures of central tendency and variability, distributions, standardization, visualization)
- basic statistical concepts (probability, probability distributions, principle of decomposing total variance into its components)
- concepts of statistical inference (population distribution, sampling distribution, point estimation and confidence interval, hypothesis testing)
- statistical tests for various research questions (covariation and correlation, regression, comparison of means, analysis of frequencies)
The lecture is accompanied by exercises in data analysis. Furthermore, students conduct and present a small-group research project.
Contact Information
Professor Gisela Böhm. E-mail: gisela.boehm@psysp.uib.no
Course offered (semester)
Autumn and spring
Language of Instruction
English.
Department
Department of Psychosocial Science.
Learning Outcomes
The course gives an introduction to quantitative research methods and statistics. The students will get an understanding of the stages of a quantitative research project. The focus of the course is on the basics of descriptive and inferential statistics. The students will learn various techniques that are used in describing, handling, aggregating, and analyzing quantitative data. They will also get a command of the principles and procedures of making statistical inferences. The students will get hands-on experience in data analysis. In addition, they will be actively involved in a research project, providing them with experience in planning and conducting quantitative research.
Contents
- descriptive statistics (measures of central tendency and variability, distributions, standardization, visualization)
- basic statistical concepts (probability, probability distributions, principle of decomposing total variance into its components)
- concepts of statistical inference (population distribution, sampling distribution, point estimation and confidence interval, hypothesis testing)
- statistical tests for various research questions (covariation and correlation, regression, comparison of means, analysis of frequencies)
The lecture is accompanied by exercises in data analysis. Furthermore, students conduct and present a small-group research project.
Pre-requirements
Due to the limited number of spaces available and special entry requirements, admission to the course is limited.
Teaching Methods
The course consists of a series of lectures. This is accompanied by exercises in data analysis. Furthermore, students conduct and present a small-group research project.
Compulsory Requirements
1. Submission of solutions to exercises in data analysis.
2. Participation in a small group research project, presentation of this project on the presentation day; submission of a summary and presentation materials for this project.
Assessment methods
Assignments in data analysis and presentation.
Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Contact Information
Professor Gisela Böhm. E-mail: gisela.boehm@psysp.uib.no