Statistics Applied to Psychology I

Code:

LPSI103

Acronym:

EAPI

Keywords
Classification	Keyword
OFICIAL	Methods

Instance: 2021/2022 - 1S

Active?	Yes
Web Page:	http://moodle.up.pt/
Responsible unit:	Psychology
Course/CS Responsible:	First degree in Psychology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
LPSIC	236	Official Curricular Structure	1	-	6	54	162

Teaching language

Suitable for English-speaking students

Objectives

At the end of this subject, students must be able:

1. To understand descriptive and inferential univariate and bivariate statistical procedures
2. To decide, critically and substantiated, the most appropriate statistical procedure
3. To use the statistical software IBM SPSS Statistics (Statistical Package for Social Sciences): construction and manipulation of a database, selection and interpretation of appropriate statistical procedures.
4. To carry out simple studies where these procedures are applied.
5. To use statistical language to understand and write research reports, with emphasis on the presentation of results.

Learning outcomes and competences

 

- Use of IBM SPSS Statistics for recording, manipulating and analyzing data
- Application of univariate and bivariate descriptive and inferential statistics
- Selection of the most adequate statistical procedure to answer a specific research question
- Report and interpretation of statistical analysis results

Working method

Presencial

Program

This subject covers the following topics:

1. Fundamental notions on variables, variable classification systems and samples
2. Create a database in SPSS.
3. Descriptive Statistics to organize and characterize data: frequency distribution, graphic representations and summarization statistics.
4. Theoretical distribution of probabilities: normal distribution.
5. Estimation theory. The notion of an estimator. Parameter estimation methods.
6. Theory of hypotheses. Mean difference analysis: Student's t-tests
7. Effect Size Measurements
8. The notion of linear correlation and its graphical representation
9. Simple Linear Regression

Mandatory literature

Lencastre,L. & Costa, P. ; Estatística Aplicada à Psicologia I On-line, 2021 (Posted in e-learning portal of the University of Porto http://moodle.up.pt, 2021)
Howell, D.C.; Fundamental Statistics for the Behavioral Sciences, Pacific Grove, 1999
Martinez, L. & Ferreira, A.; Análise de Dados com o SPSS, Lisboa: Escolar Editora, 2007
Pallant Julie; SPSS survival manual. ISBN: 0-335-20890-8
Field Andy; Discovering statistics using SPSS. ISBN: 0-7619-4452-4

Complementary Bibliography

Bryman Alan; Análise de dados em ciências sociais. ISBN: 972-774-169-X
American Psychological Association; Publication manual of the American Psychological Association. ISBN: 1-55798-790-4
Howell David C.; Statistical methods for psychology. ISBN: 0-534-51993-8

Teaching methods and learning activities

The methodology adopted in this course is based on theoretical and practical classes, in small groups of 25 students, with e-learning component. The expository method will be complemented with problem-solving and practical exercises using the IBM SPSS Statistics program. Carrying out work to apply knowledge and skills and involving the writing of short reports, following APA.

The evaluation is distributed with a final exam.

Practical group assignment is optional and has a weighting of 30% of the final grade.

For students doing practical assignment:

• the final grade will be the result of the weighted average of the final exam grade (70%) and the group work grade (30%), on a scale of 0 to 20 points;
• will have to obtain a minimum of 8 (eight) values ​​in the final exam component;

For students who do not do the practical assignment:

• will have to obtain a minimum of 10 (ten) values ​​in the final exam, on a scale of 0 to 20 points.

Software

IBM SPSS Statistics (Statistical Package for Social Sciences)

keywords

Social sciences > Psychological sciences > Psychology
Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	70,00
Trabalho escrito	30,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	76,00
Frequência das aulas	54,00
Trabalho de investigação	32,00
Total:	162,00

Eligibility for exams

• Minimal acceptable attendance is 75% of the classes.

Calculation formula of final grade

Students can choose beteewn:
- final exam
- final exam with group work
If students´s option is final exam, students must iobatin a minimum score of ten in a scale of 0 to 20. 
If students´s choice is final exam with work group, final classification will be the result, in a scale of 0 to 20, of the weighted average of the final exam score (70%) with the group work score (30%). in this case Students must obtain a minimum score of 10 in the final exam component, and there is no minimum score in the group work. The student will succed the course if attaining a minimum grade of 10 on a scale 0-20.

Special assessment (TE, DA, ...)

The students under special evaluation circumstances (in what concerns attendance) take a practical exam during the week  before the end of classes, with the rate of 20 points, which will include all the contents of the course. Having no classification, or obtaining a classification under 10 points, will lead to failing the CU.

Classification improvement

The students can take an exam to improve their final exam score, only once, until the special evaluation period of the following school year that in which they were approved, and when an exam is intended to occur.