Planning
The Planning Stage
- Understand that the planning stage is the first and one of the most important steps in any data collection process.
- Identify planning as the stage where you decide the purpose of your research, the type of data you need and how you're going to collect it.
- Recognise that a well-thought-out plan can help avoid costly and time-consuming mistakes later in the data collection process.
Identifying Goals and Objectives
- Understand the importance of clearly defining your research objectives to guide the decisions you make in planning.
- Identify your research question or problem statement as the main guide to defining your objectives.
- Recognise that clearly defined objectives can help you determine the type, amount and level of detail of data needed.
Selecting Data Collection Techniques
- Recognize that the choice of data collection technique should be guided by your research objectives.
- Understand the advantages and disadvantages of various data collection techniques including surveys, questionnaires, interviews, experiments, and observations.
- Appreciate that, often, more than one collection technique might be used in a study to ensure comprehensive and accurate data is gathered.
Planning Your Sample Size
- Understand the concept of a sample size and how it should be representative of the population you are studying.
- Identify situations where a larger sample size is beneficial for more accuracy or where a smaller sample size is adequate for exploratory research.
- Be aware that sample size will influence the effectiveness of statistical analyses conducted later on, too large or too small can both pose problems.
Ethical Considerations
- Understand the importance of considering ethical issues such as maintaining privacy and obtaining informed consent from participants at the planning stage.
- Be aware that improper handling of personal data could potentially contravene regulations like the Data Protection Act.
- Acknowledge the role of ethics in shaping the design and conduct of your data collection, including avoiding leading questions or biases.
Planning for Errors and Validity
- Anticipate potential errors and biases that could occur in your data collection, such as response bias, non-response, or inaccurate responses.
- Plan how to validate your data and check its reliability through methods such as cross-checking or repeat measurements.
- Understand that during planning, measures should be put in place to deal with possible errors and ensure the validity and reliability of collected data.