Research Methods and Techniques in Geography

Code:

GEOGR071

Acronym:

MTG

Keywords
Classification	Keyword
OFICIAL	Geography

Instance: 2024/2025 - 1S

Active?	Yes
Responsible unit:	Department of Geography
Course/CS Responsible:	Bachelor in Geography

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
GEOGR	93	study plan	1	-	6	41	162

Teaching language

Suitable for English-speaking students

Objectives

The main goal of the course is to introduce students to quantitative / statistical analysis and to outline the fundamental concepts and tools. The approach is centred on descriptive statistics, but also inferential, exploring themes related to social sciences. The course also provides a first approach to data analysis using SPSS and Excel.

Learning outcomes and competences

1.Understand the basic concepts and the fundamental procedures of the theory and practice of Statistical Science.

2.Understand how the knowledge of Statistics can be useful in the domains of Geography and other disciplines of Social Sciences and Planning, through the exploration of themes related to these domains and practical examples based on real life problems.

3.Know how to dinstinguish and correctly apply the concepts and techniques of Descriptive and Inferencial Statistics, according to the needs of each problem.

4.Obtain knowledge in terms of data collecting and data analysis techniques, through various processes (including in situ), so that data can be explored statistically.

5.Gain basic skills in the use of adequate computer software (namely Excel and SPSS) for the treatment/analysis of data, in the writing of reports, and for solving problems of Geographical Analysis.

Working method

Presencial

Program

1. General Introduction
Introduction to the Scientific Method
Sources of documental and statistical information
Classification of the techniques for collecting information
Preparing/implementing/analysing a survey
Online surveys as working tools (‘google forms’ e ‘Limesurvey’)
Introduction to the writing of reports

2. Statistical Analysis and SPSS
Fundamental statistical concepts
Descriptive Statistics: Measures and forms of representation
Introduction to SPSS

3. From Descriptive to Inferential Statistics
Sampling Theory and Probability Theory
Theoretical Models of probability distribution (normal curve)
Estimation Theory and confidence intervals
Statistical Theory of Decision - Hypothesis Tests
Parametric hypothesis tests (t test, ANOVA), normaliy tests
Non-parametric hypothesis tests (Sinais, McNemar, Wilcoxon, Mann-Whitney, Kruskal-Wallis, Wald-Wolfowitz, Ajustamento de Qui-Quadrado)

4. Regression
Introduction to the different levels of statistical analysis
Linear regression (simple and multiple)

Mandatory literature

PESTANA, Maria Helena; João Nunes GAGEIRO; Análise de Dados para Ciências Sociais, Edições Sílabo,, 1998. ISBN: ISBN: 972-618-181-X
HAINAUT Louis D; Conceitos e Métodos da Estatística, Fundação Calouste Gulbenkian,, 1997. ISBN: ISBN: 972-31-0533-0
MAROCO João; Regina BISPO; Estatística Aplicada às Ciências Sociais e Humanas,, CLIMPSI Editores, 2003. ISBN: ISBN: 972-796-065-0

Complementary Bibliography

Blalock Jr., Hubert M.; Social statistics. ISBN: 0-07-005752-4
Elifson, Kirk W.; Fundamentals of social statistics. ISBN: 0-07-115690-9
Pestana, Maria Helena; Análise de dados para ciências sociais. ISBN: 972-618-220-4
Levin, J.; Estatística aplicada a ciências humanas (2nd ed.), Editora Harper & Row do Brasil, 1977
Levin, J.; Fundamentos de estadistica en la investigacíon social, Editorial Harla., 2001
Walford, N.; Practical Statistics for Geographers and Earth Scientists, Wiley-Blackwell, 2011

Teaching methods and learning activities

The teaching methodologies aim to introduce the syllabus in a dynamic and interesting way, focused on conceptual rigor and on demonstrative and active methods. This is obtained through the stimulation of the participation and involvement of students in the resolution of the proposed problems. For this reason, the UC is taught in Theory-Practice classes, in a computer room. That way, there is a continuous relation between the conceptual approach and its practical application, through exercises made by the students individually with support from the teacher, using the proper methodologies and software. To this is added a working group component, stimulating the contact with reality (field work), that is supported in class, stimulating the debate. 

In the first part, the course will focus on reinforcing basic skills and developing new skills in descriptive statistics and in mastering new software. At the end, a test will be carried out (40% of the assessment).
In the second part, the course will focus on developing a group project (30% of the assessment).
Finally, the course will focus on developing new analysis skills.

Students will consolidate their knowledge, which will be assessed individually through two tests (40%+30%) that will include a conceptual and a practical component, with support from the selected software.
The practical projects to be developed in groups will be assessed through the submission of a report (30%).

Software

SPSS
Excel

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Teste	70,00
Trabalho prático ou de projeto	30,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	66,00
Frequência das aulas	41,00
Trabalho de investigação	55,00
Total:	162,00

Eligibility for exams

Attendance and participation in at least 75% of practical teaching hours; Students are assessed on two mandatory components: theoretical (two tests) and practical (project/practical work).
To pass, two criteria must be met: the average of the three assessment components must be higher than 10 points and each component must have a minimum of 7.5 points.
For ordinary students, the practical component is mandatory and must be completed during classes.
Exceptionally, working students may choose to complete the theoretical and practical components in a final exam. Each assessment component (two tests; practical project) must have a minimum of 7.5 points. The three components must have an average of 10 points.

Working students do not have to comply with the obligation to attend 75% of practical classes.

Calculation formula of final grade

Theoretical component - two tests: 40% + 30% = 70%
Practical component 30% - practical work.

Mandatory minimum grade of 7.5 in each component (each test and practical project).

Special assessment (TE, DA, ...)

Written test (70%). Practical work (30%).

Classification improvement

At the resit period
Written test (40%+30%). Students may appeal one of the components if they wish.
The grade obtained in the practical work counts towards the resit period (30%).

Working students who have not completed the practical work will have to take a practical resit exam.

Observations

In the case of ENEE, the SAED recommendations are followed, namely: individualized support; provision of the necessary information for consultation in digital format; extending the time available for carrying out assessment tests and/or reducing the number of questions, subdivided into periods and days according to the needs of the students; replacement of practical group work with other modalities, namely reviewing articles. These measures will be adapted to each case in initial dialogue with the students concerned.