
The aim of this training programme is to provide participants with a comprehensive understanding of data collection and sampling techniques. Each module includes a mix of lectures, interactive sessions, and hands-on exercises. Participants will work on real-world scenarios to practise designing data collection instruments and implementing sampling strategies.
- Introduction to Data Collection and Sampling:
- Overview of the importance of accurate data collection and sampling.
- Key concepts such as population, sample, and sampling frame.
- Types of Data Collection Methods:
- Detailed explanation of different data collection methods, including surveys, experiments, observations, and secondary data.
- Pros and cons of each method and appropriate contexts for their use.
- Designing Data Collection Instruments:
- How to design effective surveys, questionnaires, and data recording forms.
- Ensuring clarity, relevance, and validity in data collection instruments.
- Sampling Techniques:
- Overview of various sampling techniques, including random sampling, stratified sampling, cluster sampling, and systematic sampling.
- How to choose the right sampling technique based on research objectives and constraints.
- Sample Size Determination:
- Methods for calculating the appropriate sample size to ensure representativeness and statistical power.
- Practical exercises on determining sample sizes for different types of studies.
- Implementing Sampling Strategies:
- Step-by-step guidance on implementing sampling strategies in the field.
- Techniques for minimising sampling bias and ensuring data quality.
- Ethical Considerations in Data Collection:
- Discussing ethical issues related to data collection, including informed consent and privacy.
- Best practices for maintaining ethical standards in research.
Lectures: Detailed explanations of data collection and sampling concepts and techniques, supported by visual aids and real-world examples.
Hands-on Exercises: Practical exercises where participants design surveys, determine sample sizes, and implement sampling strategies using real-world data.
Outcome:
- Have a thorough understanding of various data collection methods and when to use them.
- Be proficient in designing effective data collection instruments.
- Understand different sampling techniques and how to choose the most appropriate one for their research.
- Be able to calculate sample sizes and implement sampling strategies that minimise bias and maximise data quality.
- Be knowledgeable about ethical considerations in data collection and how to maintain high ethical standards in their research.