Manifest variables are those that can be directly observed and measured in a study. Examples of manifest variables include height, weight, and gender.

One example of a manifest variable is height. In a study on the relationship between height and income, researchers could directly measure the height of each participant using a tape measure. This would allow them to accurately and consistently collect data on height, which could then be analyzed to determine any potential correlation with income.

Another example of a manifest variable is gender. In a study on the effects of a new medication on anxiety levels, researchers could directly observe and record the gender of each participant. This would allow them to determine whether there are any differences in the effectiveness of the medication between men and women.

Manifest variables are an important part of research, as they provide concrete, observable data that can be used to test hypotheses and draw conclusions. They are often used in conjunction with latent variables, which are underlying factors that cannot be directly observed but can be inferred from manifest variables.

For example, in the study on the relationship between height and income, researchers could use manifest variables such as education level and occupation to infer the latent variable of socioeconomic status. This would allow them to control for the potential influence of socioeconomic status on the relationship between height and income.

Overall, manifest variables play a crucial role in research by providing concrete, observable data that can be used to test hypotheses and draw conclusions. By carefully selecting and measuring manifest variables, researchers can gain valuable insights into the relationships between different factors and the underlying mechanisms at work in a given phenomenon.