Quantitative Methodologies in Consumption and Nutrition

Code:

DCCAN20

Acronym:

METQCN

Keywords
Classification	Keyword
OFICIAL	Agrarian Sciences / Nutrition Sciences

Instance: 2021/2022 - 1S

Active?	Yes
Course/CS Responsible:	Food Consumption and Nutrition Sciences

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
DCCAN	8	Oficial Plan	1	-	6	28	162

Teaching language

Portuguese

Objectives

This curricular unit aims to transmit competences to the students in order to enable them:
- To do a critical analyis of the statistical methodology used in scientific studies;
- To select the set of tools more adequate to the research they need to preform.

Learning outcomes and competences

It is intended that the students obtain knowledge and competences in applying several techniques of multivariate statistical analysis.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Previous knowledge in descriptive statistics and hypothesis testing.

Program

1. Relation between pairs of variables:

- Sensitivity and specificity, agreement and Cohen's k;

- Odds ratio and relative risk;

- Pearson's and Spearman's correlation coefficients;

- Root mean square deviation.

2. Linear regression.

3. Logistic regression.

4. ANOVA for repeated measures.

5. Principal component analysis (PCA)

6. Cluster analysis.

7. Multivariate analysis of variance (MANOVA).

Mandatory literature

Daniel Wayne W.; Biostatistics. ISBN: 0-471-16386-4
Guimarães Rui Campos; Estatística. ISBN: 972-8298-45-5 Of. Prof. Rui Guimarães

Teaching methods and learning activities

Theoretical classes are based in the expositive and interrogative methods.
Practical classes are based in the interrogative and active method. In these classes problems are placed to the students that are solved with computer aid.
Interaction and participation of the students are encouraged in all classes.

Software

SPSS
Excel

keywords

Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Exame	100,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	67,00
Frequência das aulas	28,00
Trabalho de investigação	67,00
Total:	162,00

Eligibility for exams

In order to be approved at this curricular unit, students must make two original works covering distinct subjects of the syllabus. These works should be done individually or in pairs. The first work should regard points 1, 2, 3 and 4 of the program and the second work should regard  points 5, 6 and 7.
Each work should be based on a paper (from which they do not need to be authors) published preferably in the last year, in a indexed international journal. Students should apply one of the statistical techniques mentioned in that paper to a database of their choice.
Before the oral presentation, students must give the selected papers, the presentation slides (in .pdf or .ppt format), the SPSS syntax (in .sps format), the used database (in .sav format) and an original text, made by the students, formatted as an article (.doc or .pdf) with a brief introduction, methodology and results.

Calculation formula of final grade

The evaluation of the works are based in the oral presentation of 15 minutes (total time), in the discussion that it is followed and in the characteristics of the statístical analysis preformed.

Classification improvement

Creating and presenting two different works from those that resulted in the current mark.

Observations

According to the Rector Order GR.06 / 12/2017, Article 12, point e), students are not allowed to capture images or sound of the school activities.