Reliability means in part that measurements are consistent and in turn this means that if the exact same conditions prevail in another study, for example, then the same results should be obtained. When the results are reproducible, then this is a measure of reliability. This helps to demonstrate that the results of a study are trustworthy. A study can be replicated time after time to determine the reliability of the original research methods, for example.
Researchers, for this reason, have a duty to the scientific community to report their methodology, results and findings honestly.
Next let’s look at the idea of falsifiability: this basically means that if any hypothesis has credence it has to be possible to test whether or not is correct. All researchers should test their hypotheses and prove or disprove them before they disseminate the results of their study. If a theory cannot be tested others working in the same field will not be convinced of its worth or the scientific rigour of the study. Replication must be possible to test the study’s validity. If a study cannot be replicated, this might lead other researchers to believe that the results were fabricated, and this would invalidate the whole study.
Results and findings should also be generalisable. If the results are generalisable other researchers can interpret findings and apply them to broader contexts. This makes them both relevant and more meaningful.
Some ways of establishing validity and reliability are: -
- Statistical analysis involves the collection of data and exploring it in order to work out what trends and patterns there are.
- Data triangulation adds weight to your research study because a researcher can use evidence from various sources and comparing it. This strengthens the research you have undertaken because you can compare data from interviews, documents, observations photographs and public documents, for example.
- Theory triangulation is also valuable as it enables the researcher to use various theoretical approaches to support and interpret data.
- Feedback – this is important because not everyone will hold the same opinions or have exactly the same experiences in a given situation.