Statistics II
Scholar Year: 2022/2023
| Code: |
LICFT053 |
|
| Acronym: |
ESTII |
| Scientific area: |
Investigação e Estatística, Ciências Sociais e Humanas |
| Section/Department: |
Social and Human Sciences |
| Term: |
2nd Semester |
Courses
| Acronym |
N. of students |
Study Plan |
Curricular year |
ECTS |
Contact hours |
Total Time |
| LICFT |
39 |
|
4º |
2,0 |
14 |
54,0 |
Teaching language
Portuguese
Intended learning outcomes (Knowledges, skills and competencies to be developed by the students)
- Understand concepts of Descriptive and Inferential Statistics and articulate them with research problems in Physiotherapy.
- Apply Statistical Inference methodologies to the study of populations from sample data.
- Develop computer skills related to the processing and analysis of data using the IBM SPSS Statistics software.
Syllabus
1 - Hypothesis tests for more than two independent samples
1.1 - One-way analysis of variance
1.2 - ANOVA in Kruskal – Wallis orders
1.3- Factorial ANOVA – Two Way
2 - Tests for 2 paired samples
2.1 - T test for paired samples
2.2- Wilcoxon Test
3 - Tests for more than two paired samples
3.1 - ANOVA of repeated measures
3.2 - Friedman's ANOVA
4 - ANOVA with mixed repeated measures
Demonstration of the syllabus coherence with the UC intended learning outcomes
In this course, students are expected to develop knowledge and skills that allow them to understand and apply concepts of Statistics in solving research problems in Physiotherapy.
The theoretical-practical nature of this UC allows the student to understand and analyze research problems in Statistics in the field of Physiotherapy.
Teaching methodologies
The teaching-learning strategies adopted in the curricular unit are based on a learning approach based on the following methodologies: Expository method, resolution of practical cases using IBM SPSS Statistics software.
Demonstration of the teaching methodologies coherence with the curricular unit's intended learning outcomes
The teaching/learning strategies are articulated with the objectives/expected results for this UC in the following plans:
- Information about general concepts - expository method
- Resolution of statistical problems applied to research - Resolution of practical cases
- Computer skills - application of the SPSS tool in solving practical cases
- Critical evaluation of statistical results applied to research - resolution of practical cases
Assessment methodologies and evidences
In order to obtain success in the continuous assessment regime, the student must obtain a minimum classification of 9.5 values in the set of two individual summative assessment activities.
The classification of the Curricular Unit is obtained through the following formula:
CF = AA1*50%+AA2*50%
CF=Final Classification
AA1= Evaluative Activity 1
AA2= Evaluative Activity 2
During the exam period, the student performs an individual test.
Attendance system
According to the Academic Regulation.
Software
IBM SPSS Statistics
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