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Statistics and Data Analysis 2 2017/2018

  • 5 ECTS
  • Taught in Portuguese
  • Continuous Assessment


By the end of this curricular unit, the student should be able to:
• Understand the rational underlying the procedures of statistics and data analyses using the IBM SPSS software
• Know the different techniques of statistical analyses, understand their utility, and know when to apply then, using IBM SPSS;
• Evaluate the association between variables and test prediction models
• Analyze differences between groups and between different evaluation moments;
• Recognize the assumptions and basic results of exploratory factor analyses;
• Interpret in a critical way the results of data analyses and report those results in research reports, according the APA guidelines and norms;
• Develop autonomy in using the statistical procedures requires to carry out research project, as well as in reading and interpreting results that are presented in scientific publications.

Recommended Prerequisites

Prior knowledge based on the contents learned in Statistics and Data Analysis I is recommended.

Teaching Metodology

The theoretical and practical classes will aim for a compromise between expository methodologies and active and participatory methodologies. Expository methods will be based on the use of multimedia supports, using for this purpose the IBM SPSS software, PowerPoint slides, reading and discussing documents, and managing databases. The active methods will be based on practical activities, including the exploration of databases and statistical analyzes exercises using the SPSS. These practical activities will seek the active resolution of psychology research problems as well the reporting of research results in the form of reports, individually and with mentoring from teachers.

The evaluation methodology will be continuous, with three evaluation components to be carried out throughout the semester: one written test to evaluate knowledge(worth 40% of the final grade) and two practical group tasks (which worth 30% of the final grade).

Body of Work

1. Revision of basic concepts in statistics and descriptive statistics
2. Correlational statistics
2.1. Correlation analyses
2.2. Comparison of counts and proportions
2.3. Simple and multiple regression analyses
3. Inferential statistics for comparison of means
3.1. Comparison between two conditions: parametric and non-parametric tests
3.2. Comparison between one sample and two moments: parametric and non-parametric tests
3.3. Analyses of variance with within-subjects, between-subjects and mixed designed
4. Introduction to exploratory factor analyses
5. Interpretation and reporting of research results according to the APA guidelines and norms: Text, tables and figures (transversal content).

Recommended Bibliography

- Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage Publications Ltd.
- Marôco, J. (2014). Análise estatística com o SPSS Statistics (6ª ed.). Pêro Pinheiro: Report Number.
- Martins, C. (2011). Manual de análise de dados quantitativos com recurso ao IBM SPSS: Saber decidir, fazer, interpretar e redigir. Braga: Psiquilíbrios.
- Pereira, A. (2008). SPSS – Guia Prático de Utilização Análise de Dados para Ciências Sociais e Psicologia (7ª edição). Edições Sílabo.

Complementary Bibliography

- American Psychological Association (2009). Publication manual of the American Psychological Association (6th ed.). Washington, DC: American Psychological Association.
- Cohen, B. (2008). Explaining Psychological Statistics. Hoboken, NJ: Wiley.
- Dancey, C.P. & Reidy, J. (2011). Statistics without maths for psychology (5ª ed.). Essex: Pearson Education.
- Greene, J. & D’Oliveira, M. (2006). Learning to use statistical tests in psychology. Berkshire: Open University Press.
- Pallant, J. (2016). SPSS Survival manual – a step by step guide to data analysis using IBM SPSS (6ª ed.). Berkshire: McGraw Hill Education.

Weekly Planning

S1: Presentation of the curricular unit &Revision of statistical concepts and descriptive statistics
S2: Revision of correlation analyses and chi-square analyses
S3: Linear regression
S4: Multiple regression
S5: Within and between-subjects design
S6: Tests for comparing two means for two samples: parametric and non-parametric
S7: Tests for comparing one sample in two moments: parametric and non-parametric
S8: Practical exercises & Group practical task 1
S9: Tests for comparing measures in more than one sample (i.e., between-group variance)
S10: Tests for comparing measures in more than one moment (i.e., within-group variance)
S11: Revision exercises
S12: Tests for comparing means for samples and moments (i.e., mixed design)
S13: Written test & Group practical task 1
S14: Introduction to exploratory factor analyses
S15: Revision exercises & Evaluation of the semester

Demonstration of the syllabus coherence with the curricular unit's objectives

In order to provide students with the acquisition of critical thinking skills about the usability and selection of statistical analysis procedures for the support of research, the syllabus include a variety of inferential data analysis, from tests of association between variables to group comparisons. In order that students associate these statistical procedures with research in psychology, the program contents include the analysis and reflection of data analysis results and testing of empirical hypotheses. Finally, in order to develop interpretation and reporting research results skills, the syllabus include the analysis of statistical analysis outputs and writing scientific reports according to APA norms.

Demonstration of the teaching methodologies coherence with the curricular unit's objectives

The use of expository methods enables the transmission and analysis of new contents relating to data analysis techniques using the SPSS software. These methods support the acquisition of basic knowledge in the field by the students. The use of methods involving the active participation of the students is accomplished through the analysis and interpretation of research results published in scientific papers, as well as problem solving applied to psychology with the selection and implementation of data analysis techniques. Group assignments will contribute to the acquisition of critical thinking skills about the data analysis procedures, and the interpretation and reporting of research results. The combination of these different methods will, thus, allow the accomplishment of the goals set forward for this curricular unit.

relevant generic skillimproved?assessed?
Achieving practical application of theoretical knowledgeYesYes
Adapting to new situationsYesYes
Analytical and synthetic skillsYesYes
Balanced decision makingYesYes
Bargaining abilityYes 
Commitment to effectivenessYes 
Commitment to qualityYes 
Ethical and responsible behaviourYesYes
Event organization, planning and managementYesYes
Foreign language proficiencyYes 
Information and learning managementYesYes
Initiative and entrepreneurship capabilityYes 
IT and technology proficiencyYesYes
Problem Analysis and AssessmentYesYes
Relating to othersYes 
Research skillsYesYes
Written and verbal communications skillsYes 
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