RM-U9A

Unit 9 Assignment Name: 1 Ways that a correlation between X and Y could be interpreted. Links between two variables X and Y can be fascinating but by no means demonstrate a causal relationship without more analysis. There are primarily three ways such a correlation can be interpreted:Causal Direction from X to Y: This way of thinking says that X is the cause of Y. In this case, the relationship is meant to be direct with Y being a result of changes in X. For example, more hours for studying (X) could improve exam scores (Y) (James & Irvine, 2020).Causal Direction from Y to X: However, the situation could be that Y is the cause of X. For instance, a student could get better exam scores (Y) and then study harder (X) either to boost their confidence or for a feedback loop.Presence of Confounding Variables: In most cases, a correlation between two variables is due to third variable, or a confounder. These moderators can affect both X and Y, which leads to the occurrence of spurious correlation that is the consequence of a cause-and-effect relationship between X and Y. Links between two variables X and Y can be fascinating but by no means demonstrate a causal relationship without more analysis. There are primarily three ways such a correlation can be interpreted:Causal Direction from X to Y: This way of thinking says that X is the cause of Y. In this case, the relationship is meant to be direct with Y being a result of changes in X. For example, more hours for studying (X) could improve exam scores (Y) (James & Irvine, 2020).Causal Direction from Y to X: However, the situation could be that Y is the cause of X. For instance, a student could get better exam scores (Y) and then study harder (X) either to boost their confidence or for a feedback loop.Presence of Confounding Variables: In most cases, a correlation between two variables is due to third variable, or a confounder. These moderators can affect both X and Y, which leads to the occurrence of spurious correlation that is the consequence of a cause-and-effect relationship between X and Y. 2 Confounding variable. Confounding variables are external factors that both X (independent variable) and Y (dependent variable) in a study are affected by, thus, resulting in a spurious influence between them. The confounder will make it difficult to see the actual effect that X has on Y or it may even create an untrue correlation in a situation where none exists. Determining and managing for confounders is critical to make sure one has valid and precise causal associations in research.Confounding variables are external factors that both X (independent variable) and Y (dependent variable) in a study are affected by, thus, resulting in a spurious influence between them. The confounder will make it difficult to see the actual effect that X has on Y or it may even create an untrue correlation in a situation where none exists. Determining and managing for confounders is critical to make sure one has valid and precise causal associations in research. 3 Ways that a correlation between time spent outdoors and happiness could be interpreted The relationship between spending time outdoors and experiencing happiness can be explored from several angles...