Quantitative methods: Experimental design and analysis

Ph.D. -course

Course description

Course content

General content

The present course is sub-course B; one of three sub-courses of the overarching course on quantitative methods that covers a broad range of quantitative research methods and statistical analysis techniques. Sub-course B is on experimental design and analysis (1 ECTS).

This sub-course will discuss the strengths and weaknesses of the experimental approach, describe the various components and different types of experimental designs. Principles of experimental data analysis will be presented.

Performing an experiment is the only research method suited for drawing causal inferences about a research question. By using an experimental design that provides a strict operationalization, randomization, control and manipulation of variables, we can perform statistical analyses that allow us to distinguish the signal from the noise, and identify causal and interactive relationships in our data set. This course will discuss the strengths and weaknesses of the experimental approach, describe the various components and different types of experimental designs. Common problems in experimenter-participant communication and how to deal with them will also be discussed. Group work sessions will discuss the issues and relate them to examples that are provided and to your own datasets or designs. Experiment programming software will be demonstrated and discussed. Principles of experimental data analysis will be presented, including how a data set is organized, what assumptions underlie various statistical tests, parametric vs. non-parametric statistics, as well as several methods to analyze categorical and continuous predictor variables (t-test, ANOVA, Mann-Whitney-U-test, correlation, linear regression). Demonstrations or hands-on assignments of power analysis, experiment programming and analysis (in SPSS). On signing up you will be asked to fill out a questionnaire that will help us to adjust the teaching to the needs of the participants.

Type of course

Methods

Learning outcomes

General learning objectives

This course seeks to promote and facilitate the rigorous use of quantitative approaches and good practices in designing and analyzing psychological research questions.

Knowledge

After completion of the course, the candidate

- Has knowledge of various approaches of data collection using experimental designs.

- Has knowledge of various approaches of analyzing experimental data structures.

Skills

After completion of the course, the candidate

- Can evaluate and select appropriate data analytical tools and software solutions.

- Can evaluate and select appropriate analysis in experimental research.

- Can draw appropriate conclusions from experimental research.

General competence

After completion of the course, the candidate

- Can master experimental research designs.

- Can reflect upon different approaches to quantitative research methodology

Study period

Spring 2018, 12-14 March.

Credits (ECTS)

1 ECT

Course location

Faculty of Psychology, University of Bergen
Language of instruction
English
Course registration and deadlines

The course is not currently planned for this semester. For a list of planned courses visit PhD Courses and Seminars | Graduate School of Human Interaction and Growth | UiB

Pre-requirements

Master Degree in disciplines relevant to educational sciences, psychology and public health.

  1. Participants must answer a brief questionnaire when signing up for the course, in order to provide information for adjusting the course topics and depth.
  2. Participants must be prepared to present their research question and approach to data collection
  3. On the second day of the course, the experiment programming software packages E-Prime and PsychoPy will be demonstrated. Participants who would like to try out the software on their own computers, are recommended to download and install a trial version from http://pstnet.com/request-a-demo/. PsychoPy is open-source software, and downloadable free of charge from http://www.psychopy.org. SurveyXact is licensed by UiB and accessible at: https://feide.survey-xact.no.
  4. On the second day of the course, there will be hands-on assignments in performing analyses on a provided data set. Participants must bring a laptop computer with the statistics software package SPSS installed. All university employees can download this software from https://tjinfo.uib.no/program.
Compulsory Requirements
Participation and assignments to be completed on individual basis or in small groups. Plenary presentations.
Form of assessment

Active participation and presentations in class. 80% attendance required.

Pass or fail.

Who may participate
The course targets primarily PhD candidates at the Faculty of Psychology, UiB. Other groups can apply for participation.
Supplementary course information

Learning activities:

Experimental designs and different analysis approaches will be presented in lectures and led discussions, small-group discussions, and guided workshops with assignments to be completed on individual computers. Some assignments will be performed in group discussions, while other assignments will assume that work is performed individually or in small groups, and presented in plenary on the last day of the course.

Academic responsible
Gisela Bøhm, Department of Psychosocial Science.
Lecturers
Sebastian Jentschke, Department of Biological and Medical Psychology, Vebjørn Ekroll and Bjørn Sætrevik, Department of Psychosocial Science, UiB.
Reading list
To be provided in January 2018.