Universitat Internacional de Catalunya
Methodology Applied to Psychology
Other languages of instruction: Catalan, English
Teaching staff
Course Coordinator: Dr Carlos Gª Forero (cgarciaf@ui.es)
Introduction
Statistics and Psychology have been closely related since the inception of both disciplines. The foundations of Scientific Psychology were conjoined with the beginning of methods for analyzing experimental data. Personality Psychology, Psychophysics or Psychometrics theoretical developments are rooted on results based on the creation of specific statistical techniques by psychologists.
Competence in analysing and analysing quantitative is essential in Health Sciences. Psychology researchers and applied professionals must be able to make inferences from data and to critically assess statistical results to keep up with the latest changes in their fields
Pre-course requirements
It is convenient to have passed the subject Introduction to Psychology Research.
Objectives
General objectives
- Develop an understanding of the importance of data analysis in the context of Psychology and Health Sciences
- Provide tools to appraise the potential and limitation of statistical analysis methods.
- Provide knowledge of the main techniques for statistical analysis of quantitative data.
Specific objectives:
- Systematise procedures for defining research questions as statistical hypotheses.
- Apply statistical analyses for answering research hypothesis
- Develop tools for creating analysis plans
- Establish a framework for understanding techniques for analysing differences and associations
- Appraise the limitations of statistical analysis.
- Write research reports based on statistical information
Competences/Learning outcomes of the degree programme
- CB03 - Students must have the ability to bring together and interpret relevant data (normally within their area of study) in order to issue judgements that include a reflection on relevant issues of a social, scientific and ethical nature.
- CB04 - Students must be able to convey information, ideas, problems and solutions to both specialised and non-specialised audiences.
- CE02 - The ability to write reports on the results obtained during the evaluation process using Psychology-specific language.
- CE03 - The ability to make adequate decisions about what Psychology-specific methods and measuring instruments to use in each situation or evaluation context.
- CG01 - Capacity for critical and creative thinking, and capacity to investigate and adopt a scientific and ethical approach in distinct professional settings.
- CG02 - The ability to make critical and well-founded judgements and assessments as part of the decision-making process.
- CG03 - The ability to read scientific literature in a critical, well-founded manner, take into account its provenance, situate it within an epistemological framework and identify and contrast its contributions in relation to the disciplinary knowledge available.
- CG06 - Flexibility, respect and discretion in the use of data corresponding to people, groups and organisations.
- CT02 - The capacity to solve problems.
- CT03 - The capacity for analysis and synthesis.
- CT04 - The capacity to work in a team
- CT05 - The ability to reason and assess situations and results from a critical, constructive point of view.
Learning outcomes of the subject
After passing the course, students must be able to
1. Autonomously obtain information about data analysis in the research literature.
2. Set up a data analysis plan within the context of behavioural and health sciences, deciding appropriately between differences and relationships, and identifying the correct statistical techniques for comparing and associating variables.
3. Interpret correctly statistical results using the software for statistical analysis used in the subject, being capable of choosing and applying the correct technique.
4. Critically assess research reports, being able to differentiate their elements, and learning where to find strengths and weaknesses.
5. Work systematically in statistical data treatment to avoid errors and reach rigorous conclusions.
6. Write technical reports based on statistical results.
7. Preparing and processing data following statistical database conventions.
Syllabus
The course begins reviewing basic concepts in descriptive statistics and moves on to concepts of statistical inference (sampling, estimation, and hypothesis testing). Then, the most general and useful statistical techniques in behavioural and health sciences are explained, structured in two broad families:
1) Comparison techniques: Z-tests, t-tests and ANOVA models
2) Techniques for associations: regression and contingency tables.
Each method is conceptually explained, emphasising the logic of the statistical technique, objectives and performance. Then, the technique is applied using statistical analysis software of widespread use in professional settings and academia (SPSS; Statistical Product and Service Solutions).
CONTENTS
Block 1. Descriptive statistics and concepts of statistical
- General concepts of Descriptive Statitics
- Correlation and regression
- Probability, random variable, statistical distribution
- Inference, estimation and statistical testing
Block 2. Analysing comparisons
- Statistical tests for comparing proportions
- Statistical tests for comparing means
- Statistical testing for more than two means: ANOVA models
Block 3: Analyzing relationships
- Regression
- Contingency tables
Bibliography and resources
The following manuals are compulsory bibliography:
1) Pardo A, Ruiz MA y San Martín R (2015). Análisis de datos en ciencias sociales y de la salud (vol I, 2ª ed). Madrid: Síntesis.
2) Pardo A y San Martín R (2015). Análisis de datos en ciencias sociales y de la salud (vol II, 2ª ed).vMadrid: Síntesis
The course will follow these materials carefully. The students are expected to have read session materials beforehand.
Evaluation period
- E1 28/05/2021 A01 10:00h
- E2 28/06/2021 A14 12:00h