Research Methodology II

Code:

GD53

Acronym:

GD53

Keywords
Classification	Keyword
CNAEF	Social and Behavioral Sciences

Instance: 2019/2020 - 2S

Active?	Yes
Course/CS Responsible:	2nd Cycle in Sports Management

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
2CGD	33	Official Plan	1	-	3	20	81

Teaching language

Suitable for English-speaking students

Objectives

1º Obtain a systemic knowledge in fundamental aspects of research (establishing problems and hypothesis, research designs, research project building, links among purposes-hypothesis-design) and their association to quantitative data analysis.

2º Consolidate data analysis knowledge in the following topics: (i) exploratory and descriptive data analysis; (ii) hypothesis testing, from t tests to ANOVA I, parametric and non-parametric; (iii) correlation and multiple regression.

3º Sound knowledge in data control and analysis methods.

4º Obtain proficiency in the use of Excel and SPSS softwares.

Learning outcomes and competences

The syllabus contents are coherent with curricular unit aims, as they enable students to understand and evaluate the relevancy of research methods and quantitative data analysis in their future work in other curricular units as well as in their final dissertation. Starting from a theoretical basis concerning multiple research questions and data analysis, students with acquire sufficient knowledge in diverse research designs all context specific. We also aim also to have students with ample independent knowledge to work with Excel and SPSS. Syllabus contents will give students opportunities to present published papers allowing for the critical analysis of their content given the knowledge they have.

Working method

Presencial

Program

1. Research process: (i) fundamental ideas; (ii) problems, hypothesis and design; (iii) the research Project; (iv) sample size, data quality control e steps in data analysis; (v) research designs of single and multiple groups.


2. Exploratory data analysis: (i) fundamental ideas; (ii) graphical representations; (iii) central tendency and variation measures; (iv) examples in Excel and SPSS.


3. Inferential analysis: (i) hypothesis testing,  and p-value; (ii) t tests and non- parametric measures; (iii) bivariate and partial correlation; (iv) simple regression, ANOVA I; (v) examples in Excel and SPSS.


4. Data quality control (classical test theory)

Mandatory literature

Andrew D, Pedersen P, McEvoy C ; Research methods and design in sport management, Human Kinetics, 2011
Skinner J, Edwards A, Corbett B ; Research methods for sport management, Taylor & Francis, 2011
Pestana MH, Gageiro JN ; Análise de dados para ciências sociais. A complementaridade do SPSS, Edições Sílabo, 2003
Pedhazur EJ, Schmelkin LP ; Measurement, design and analysis, Lawrence Erlbaum Associates, 1991
Thomas J, Nelson J, Silverman L ; Research design in physical activity, HUman Kinetics, 2011

Teaching methods and learning activities

Classes have a triple format. Firstly, theoretical presentation and discussion of syllabus contents. Secondly practical sessions include the use of Excel and SPSS dealing with problem solving. Thirdly, all master students will present a published paper of his/her interest, putting themselves in a “researcher skin”.

A written exam concerning all syllabus contents will be used to assess their knowledge.

Evaluation Type

Evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	90,00
Participação presencial	10,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	61,00
Frequência das aulas	20,00
Total:	81,00

Eligibility for exams

To be able to attend the final exam all students must be present in 75% of all classes.

Calculation formula of final grade

Final grade is obtained according to the following formula: (exam*90+Participation*10)/100.