Now that you know that your questions are generating reliable data, the next step is to check validity.
There are five main ways that researchers can make sure that the conclusions they’re drawing from their data are valid. You can click on the name of each type of validity to learn more about them and how you should test for them.
Face validity refers to the extent to which a survey measures what it aims to.
Content validity measures how well a survey covers the various aspects of a topic that it aims to understand.
Criterion validity measures how well the results of your survey can be used to predict another outcome that you would expect to be related.
Discriminant validity can help you make sure that topics that are not supposed to be related are actually not related.
Internal validity measures whether the study design rules out other factors, so that the causal relationship (cause/effect) being tested is not influenced by them.
External validity measures how well the results from your study can be applied to other situations, groups, or events.
Personal Project
Once you have learned more about these different types of validity, consider which tests are important for your survey. Think about the purpose of your research, and what you hope to test by asking these questions to determine which validity checks you should perform. After you have completed these tests, you can move on to your data analysis and start to draw conclusions to ultimately answer your research questions.
