Quantitative Methodologies in Consumer Sciences

Code:

CAGR4014

Acronym:

CAGR4014

Level:

400

Keywords
Classification	Keyword
OFICIAL	Agrarian Sciences

Instance: 2025/2026 - 1S

Active?	Yes
Responsible unit:	Department of Geosciences, Environment and Spatial Plannings
Course/CS Responsible:	Master in Food Science and Technology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:TCA	3	Official Study Plan	1	-	6	42	162

Teaching language

Suitable for English-speaking students

Objectives

Students are expected to be able to apply data analysis techniques in concrete contexts of consumer sciences. Perform the techniques and analyze appropriate information obtained through the computer application IBM SPSS Statistics (SPSS).

Learning outcomes and competences

At the end of the semester the student is expected to be able to use SPSS autonomously, in particular at the following levels:

-Data entry and encoding of variables;

-Application of descriptive statistics to summarize the data;

-Application of parametric comparison tests and non-parametric, with interpretation of results.

Working method

Presencial

Program

Introduction to data analysis. Sampling and data logging. Variable coding and frequency tables.
Descriptive statistics (statistics, tables and graphs).
Foundations of statistical inference. Parametric and non-parametric tests tests (testing for normality, testing for homogeneity of variance, t-tests, Chi-square test, Mann-Whitney test, Kruskal-Wallis, Wilcoxon test and the Friedman test).
Introduction to regression. Linear regression
Analysis of variance – ANOVA: 1 factor 2, repeated measures factors.
Multiple comparison tests: LSD, Tuckey and Bonferroni.
Introduction to multivariate analysis: principal components factor analysis
Introduction to SPSS and its use: presentation of the various screens, data entry, coding of variables, descriptive statistics (statistics, graphs and tables), parametric and non-parametric comparison tests, encoding of multiple response questions, linear regression, ANOVA,  factor analysis and assessment of internal consistency.

Mandatory literature

Naresh Malhotra; Marketing Research: An Applied Orientation, Global Edition, Pearson Education Limited, 2019. ISBN: 9781292265636
João Marôco; Análise Estatística com o SPSS Statistics (8ª Edição) , ReportNumber, 2021. ISBN: 9789899676374

Teaching methods and learning activities

Theoretical exposition of the techniques and software, complemented by practical lessons using personal computer, where students apply the techniques in SPSS, with presentation and discussion of the information produced. In addition to the examples presented, illustrating the application of the techniques and the use of SPSS, students will need to perform exercises in the classroom, with direct application of apprehended knowledge. Additionally, students will need to develop the analysis work, followed by a final design, where a wide range of statistical techniques must be applied, independently, using the SPSS. Part of the work will be distributed, discussed and presented through the internet, based on distance learning platforms. Reports shall be drawn for classroom work and for the final project.

Software

IBM SPSS Statistics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	60,00
Trabalho escrito	20,00
Trabalho prático ou de projeto	20,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Elaboração de projeto	20,00
Frequência das aulas	42,00
Trabalho escrito	6,00
Estudo autónomo	94,00
Total:	162,00

Eligibility for exams

The frequency of discipline requires the completion of at least 75% of practical lessons, and taking of the work practices.

Calculation formula of final grade

The final grade will be calculated on the basis of the following elements:
20% individual exercise sheets,
20% final project (oral presentation and report),
60 % Exame (Minimum classification of 8,0 val to add practical component)

Special assessment (TE, DA, ...)

Only for the exam

Classification improvement

Only for the exam

Observations

Naresh Malhotra; Marketing Research: An Applied Orientation, Global Edition, Pearson Education Limited, 2019.

João Maroco; Análise Estatística com o SPSS Statistics, 8ª edição, ReportNumber, 2021.

 
Jury of the UC:
Luís Miguel Cunha
Susana Fonseca
Albano Beja Pereira