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The independent variables selected in a study are expected to cause changes in the dependent variables because they represent potential causes or influences on the outcome. For example, if a researcher is looking at how income levels affect mental health they would likely select income as an independent variable with mental health being the dependent variable. This is because researchers expect that changes in income will have some effect on mental health outcomes and therefore want to measure any connection between these two factors.
In addition, by selecting independent variables, researchers can also control for other potential influences that could be affecting their results such as gender, age, education level, etc.—ensuring that any observed correlation between the independent and dependent variables is more likely due to their relationship rather than outside interference. This helps to identify causal relationships between different factors which can be used to draw meaningful conclusions from data collected during a study.
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