Collection of Quantitative/Qualitative Data

Collection of Quantitative and Qualitative Data

Understand the difference between quantitative and qualitative data in an experimental context, with the former being numeral and measurable, and the latter being descriptive and observed.
Quantitative data, often collected using scientific instruments, provides measurable and statistical evidence that can be analysed numerically. An example would be measuring the effect of different light wavelengths on plant growth in millimetres.
Qualitative data, on the other hand, is generally collected through observations, interviews, or case studies. This data helps understand the descriptive attributes of your investigation that cannot be simply expressed in numbers. An example might be noting the colour changes in a chemical reaction.
The data collected should be relevant and sufficient to support your experimental outcomes. Selection of data type largely depends on the nature of your investigation.
Use data tables to effectively organise and record quantitative data during the experiment.
For qualitative data, it’s important to maintain a robust system of note-taking to record observations accurately.
Ensure all collected data is reliable and accurate. Repeat experiments or observations where possible to increase reliability.
Use data analysis techniques such as statistical test to interpret the collected data.
Always consider the limitations and potential errors in data collection and how this will impact your conclusions.
Ultimately, the aim is to interpret the data in a manner that either supports or refutes your initial hypothesis.

Remember - choice of data depends on your investigation. Quantitative data is numeric and measurable, while qualitative data is descriptive. Both types can be integral in supporting your hypothesis through the analysis of collected evidence.