
Data Collection Methods
Code
200087
Academic unit
NOVA Information Management School
Credits
7.5
Teacher in charge
Weekly hours
2.0
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Objectives
This course aims to address a set of methodologies that support any process of data collection, with main emphasis on the context in which the data collection is performed by sampling.
It is addressed the issue related to the definition of the target populations and the establishment of sampling frames, presented the main sample designs of empirical and probabilistic character and also analyzed methods for prevention and treatment of the main non-sampling errors.
With this course students should be able to design a methodology that supports the collection of data, with particular emphasis on the context of a marketing research.
At the end of the course the student should achieve the following learning objectives:
- Identify and differentiate the data collection methods.
- Set a target population and constitute a sampling frame.
- Identify preventive and corrective measures for non-sampling errors.
- Understand and apply non probabilistic sampling methods.
- Understand and apply probabilistic sampling methods.
- Develop the appropriate sampling methodology for each situation.
- Calculate the size of a sample.
- Estimate characteristics of the population based on sample information.
- Calculate precision measurements for a particular estimation.
Prerequisites
Statistics.
Subject matter
- Introduction to data collection
- Target population and sampling frame
- Non-sampling errors
- Non probabilistic sampling
- Probabilistic sampling
Bibliography
Malhotra, Naresh K., Birks, David F. (2007). Marketing research: an applied approach. Third European edition. Harlow: Prentice Hall/Financial Times.
Vilares, M., Coelho, P.S. (2011). Satisfação e Lealdade do Cliente – Metodologias de avaliação, gestão e análise. Escolar Editora.
Teaching method
The curricular unit is based on theoretical and practical lessons, including presentation of contents (concepts and methodologies), presentation of practical cases, discussion of methodologies and resolution of exercises.
Evaluation method
Exam (60%) + Project (with presentation and discussion) (40%)
The project of the course includes the elaboration and presentation of a report, which must be discussed with the teacher. This project includes the design of a data collection method for a particular marketing problem, namely the design and the calculation of the dimension of a sample.
To ensure approval it is mandatory to reach a minimum score of 9.5 values (out of 20) in each assessment element.
Courses
- Information Analysis and Management
- PostGraduate in Information Systems Governance
- Risk Analysis and Management
- Marketing Intelligence
- PostGraduate Information Systems and Technologies Management
- Knowledge Management and Business Intelligence
- PostGraduate in Information Management and Business Intelligence in Healthcare
- PostGraduate in Marketing Intelligence
- Marketing and Research and CRM
- PostGraduate in Enterprise Information Systems
- PostGraduate in Information Analysis and Management
- PostGraduate in Digital Enterprise Management
- Information Systems and Technologies Management
- PostGraduate Risk Analysis and Management
- PostGraduate in Knowledge Management and Business Intelligence
- PostGraduate Marketing Research e CRM
- PostGraduate Digital Marketing and Analytics