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.