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What are some examples of correlation If you spend lots of time studying you will get a better grade. Hopefully true, but time spent does not always equal improvement. Taller people need bigger shoes and smaller people need smaller shoes. The more coffee you drink, the longer you will stay awake.
Correlation Analysis Example By analyzing how various independent variables (such as salary or benefits) impact a dependent variable (such as employee satisfaction or eNPS), employee survey vendors can gain valuable insights to improve employee engagement and retention.
What is an example of a correlational study? An example of a correlational study might be a study that asks, Is there a relationship between technology use and mental health? However, while the study can find a relationship between these things, it cannot say whether one causes the other.
Correlational studies aim to find out if there are differences in the characteristics of a population depending on whether or not its subjects have been exposed to an event of interest in the naturalistic setting.
Consider hypothetically, a researcher is studying a correlation between cancer and marriage. In this study, there are two variables: disease and marriage. Let us say marriage has a negative association with cancer. This means that married people are less likely to develop cancer.
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Correlational research quantifies the strength and direction of the relationship between two variables. At least two variables are measured. Can be used to predict future events when tested using regression. Provide data that are consistent or inconsistent with scientific theories.
A correlational research design investigates relationships between variables without the researcher controlling or manipulating any of them. A correlation reflects the strength and/or direction of the relationship between two (or more) variables. The direction of a correlation can be either positive or negative.
There are three basic types of correlational studies that are used in eHealth evaluation: cohort, cross-sectional, and case-control studies (Vandenbroucke et al., 2014).

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