2024
Survey Sampling
Name: Survey Sampling
Code: MAT13616M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Mathematics
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Regime de Frequência: Presencial
Sustainable Development Goals
Learning Goals
In this course the student will:
• Study the key issues about planning and executing a sampling plan, and the theory of estimation for the most commonly known sampling designs.
• Acquire some basic notions on estimation and sampling techniques useful for applications.
In the end of the course, the student must be able to:
• Plan, organize, implement and conduct a survey sampling study;
• Evaluate and criticize misuses of sampling methods;
• Work alone and in group;
• Correctly use software for sampling designs and analysis
• Study the key issues about planning and executing a sampling plan, and the theory of estimation for the most commonly known sampling designs.
• Acquire some basic notions on estimation and sampling techniques useful for applications.
In the end of the course, the student must be able to:
• Plan, organize, implement and conduct a survey sampling study;
• Evaluate and criticize misuses of sampling methods;
• Work alone and in group;
• Correctly use software for sampling designs and analysis
Contents
1. Main steps on planning a sampling design and the selection of sampling units.
2. Methods for data collection in survey sampling.
3. Treatment of non-responses and measurement errors.
4. Simple random sampling: basic ideas and estimation.
5. Systematic random sampling stratified random sampling and post-stratification.
6. Unequal probability sampling and sub-sampling designs.
7. Clusters and multi-step sampling designs.
2. Methods for data collection in survey sampling.
3. Treatment of non-responses and measurement errors.
4. Simple random sampling: basic ideas and estimation.
5. Systematic random sampling stratified random sampling and post-stratification.
6. Unequal probability sampling and sub-sampling designs.
7. Clusters and multi-step sampling designs.
Teaching Methods
Teaching methodologies:
A mixture of theoretical and practical lectures on the blackboard and with support of e-learning tools and visual aids.
Introductory concepts are given using real examples of different areas of applications to show the relevance of programmatic contents.
The exercises will focus on solving problem strategies to motivate students and to show the utility of sampling techniques.
Attendance, classroom participation and continued students assessments are encouraged.
Evaluation:
The continuous evaluation is made with various homework assignments (50%) and a final project (50%). Sometimes homework and the final project may be done in group. The final project should be presented in a written and oral form in the classroom. If continuous evaluation is not feasible for the student, a final examination is possible (50%), but a project is still required for final grade (50%).
A mixture of theoretical and practical lectures on the blackboard and with support of e-learning tools and visual aids.
Introductory concepts are given using real examples of different areas of applications to show the relevance of programmatic contents.
The exercises will focus on solving problem strategies to motivate students and to show the utility of sampling techniques.
Attendance, classroom participation and continued students assessments are encouraged.
Evaluation:
The continuous evaluation is made with various homework assignments (50%) and a final project (50%). Sometimes homework and the final project may be done in group. The final project should be presented in a written and oral form in the classroom. If continuous evaluation is not feasible for the student, a final examination is possible (50%), but a project is still required for final grade (50%).
Teaching Staff
- Anabela Cristina Cavaco Ferreira Afonso [responsible]
Certificações
