Class Métodos de Investigação em Neuropsicologia Aplicada II

  • 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.

  • Code


  • 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 Regression

    PC4.4. Mediation Models
    PC4.5. Moderation Models
    Note. PC = program contents

  • 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 type

    LO8. Present and interpret the results obtained from data analysis clearly
    LO9. Use a statistical analysis software appropriately and effectively.
    Note: LO = learning objective

  • 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).

  • 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. 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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