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Presentation
Presentation
This Course enables students to develop skills in data analysis for research in Psychology, focusing on techniques of quantitative data analysis in the field of psychometrics and inferential statistics, as well as qualitative data analysis.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Master Degree | Semestral | 5
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT789-25057
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
PC1. Qualitative data analysis methods: Thematic analysis
PC2. Quantitative data analysis methods: Descriptive statistics and inferential statistics
PC3. Psychometrics
PC3.1. Concept of psychometric scales and measurement theory in psychometrics
PC3.2. Psychometric validation of measurement tests: Exploratory Factor Analysis and Confirmatory Factor Analysis
PC4. Inferential Statistics:
PC4.1. Univariate and Multivariate Analysis of Variance
PC4.2. Analysis of Variance with Repeated Measures
PC4.3. Linear relationship between two variables: Correlation, Simple and Multiple Linear RegressionPC4.4. Mediation Models
PC4.5. Moderation Models
Note. PC = program contents
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Objectives
Objectives
LO1. Conduct a Qualitative data analysis
LO2. Understand psychometric theories and underlying assumptions in scale construction
LO3. Conduct a psychometric analysis of a scale and interpret its results
LO4. Comprehend the relationship between conceptual hypothesis, study design, statistical procedure, and statistical hypothesis
LO5. Apply Analysis of Variance and Multivariate Analysis techniques to problems in the domain of Psychology with within-subject and between-subjects samples
LO6. Apply Simple Linear, Multiple, Mediation, and Moderation Regression models to problems in the domain of Psychology
LO7. Choose and apply different statistical procedures considering research objectives and data typeLO8. Present and interpret the results obtained from data analysis clearly
LO9. Use a statistical analysis software appropriately and effectively.
Note: LO = learning objective
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Teaching methodologies and assessment
Teaching methodologies and assessment
The classes of this course, of a theoretical-practical nature (TP), have a primarily applied component, in which students apply the theoretical skills acquired through practical activities such as conducting, analyzing, and discussing applied data analysis procedures. The practical application of the learned concepts will also be carried out using data from a study developed by the students themselves in the course of Research Methods I, allowing them to explore all phases of a research process over the two semesters.
To engage students in research conducted in the field of Psychology, published studies in international journals that utilize the taught models and analytical techniques will be presented. Additionally, whenever possible, students will be involved in ongoing research projects at the Research and Development Unit (HEI-Lab).
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References
References
Braun, V., & Clarke, V. (2023). Toward good practice in thematic analysis: Avoiding common problems and be (com) ing a knowing researcher. International Journal of Transgender Health , 24 (1), 1-6. https://doi.org/10.1080/ 26895269.2022.2129597 .
Field, A. (2017). Discovering statistics using IBM SPSS Statistics (5 th Ed.) . London: Sage.
Flick, U. (2009). Introdução à Pesquisa Qualitativa (3.a Ed.). Porto Alegre: Artmed.
Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach . New York:Guilford Publications.
Maroco, J. (2018). Análise estatística com o SPSS statistics ( 7a Ed. ) Lisboa: ReportNumber.
Bardin,L. (2004). Análise de Conteúdo . Lisboa: Edições 70.
Tabachnick, B. & Fidell, L. (2006). Using multivariate statistics . USA: Pearson International.
Watt, R., & Collins, E. (2019). Statistics for Psychology: A Guide for Beginners (and everyone else). SAGE Publications Limited.
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Office Hours
Office Hours
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Mobility
Mobility
No