Discussion - Week 6

COLLAPSE

Focus: Variable Relationships

When considering the relationships between variables, it is a common mistake to assume causation when a correlation is present. A high correlation between variables does not necessarily indicate causation. A study may show a positive correlation between salary and quality of work of individual employees in that the more employees are paid, the better their performance. However, one cannot assume causation because other factors, such as training, collaboration, and IT solutions, may impact the quality of an individual's work. Perhaps it would be prudent to consider the possible correlation between employee training and the quality of work of individual employees. Should a researcher safely assume that a causal relationship exists here: the better training employees receive, the better their performance? While strong correlations prompt researchers to take notice of possible causality, researchers must also be aware of attentional bias and prior beliefs when interpreting correlations. It is, therefore, essential to examine how causation is established.

You will distinguish between the two concepts of causation and correlation and apply them to your potential doctoral study.

By Day 3:

• State the potential research questions and hypotheses for your doctoral study research.
• Present how your study's constructs are correlational and not causal unless you have an actual experimental condition. Defend all causal conditions if you have a real observed need with all standard components.
• Finally, correlation analysis will examine how and whether your envisioned doctoral study's questions will be sufficiently answered.