ensuring validity and reliability in quantitative research

This is about approaching your quantitative research from an entirely objective and unassuming standpoint – which can be really challenging, since unintentional bias is often a problem in quantitative studies. 💡 Avoiding bias and leading the participants Getting others who are entirely removed from your research to test the survey is a great workaround – this will also allow you to check their responses do indeed answer or confirm the underlying hypothesis.Īt PFR, as part of our remote unmoderated task service, we regularly offer our clients the chance to test their surveys or card sorts with a small number of participants before sending it to a large group of people. Questions must be straightforward, free of jargon, and must mean the same thing to all who read it. As a rule, quantitative research is usually unmoderated, so if your questions are ambiguous or do not accurately reflect what you intend to ask, there is no opportunity to provide further explanation or for participants to ask questions. It sounds obvious, but the question type and wording itself truly steers the validity of quantitative research.

None of these potential outcomes are ideal, and all severely affect the validity of the overall results. Chances are the participant will get to this type of question and: The research method you select needs to accurately reflect the type, format and depth of data you need to capture in order to suitably answer your questions.Īs an example, if you are running research with participants that are lower on the digital spectrum and aren’t confident online, I would advise against incorporating complex question types, such as large grids, into your survey. This one is fundamental to securing valid results, as it sets the tone for the entire project. Of course, there are ways to avoid this and ensure your quantitative research gets the thumbs up from both the wider industry you operate in and the stakeholders commissioning or approving the project. In summary, research isn’t helpful at all when it doesn’t answer the questions you intend it to! In fact, it’s an absolute waste of time and budget if this is the case.

For research to be deemed credible, and to ensure there is no uncertainty on the integrity of the data, it is essential to achieve high validity. Validity within quantitative research is a measure of how accurately the study answers the questions and hypotheses it was commissioned to answer.

Ensuring validity and reliability in quantitative research