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Q: How can variables be correlational but not causal?
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How does experimental research differ importantly from correlational research methods?

Experimental research involves manipulating variables to determine cause-and-effect relationships, while correlational research examines the relationship between two or more variables without manipulation. Experimental research allows for greater control over variables and enables researchers to draw stronger causal inferences compared to correlational research.


How does a Correlational experiment differ from a quasi experiment?

A correlational experiment examines the relationship between variables without manipulating them, while a quasi experiment involves manipulating an independent variable but lacks random assignment of participants to conditions. So, a correlational experiment focuses on the association between variables, while a quasi experiment allows for some degree of causal inference due to the manipulation of an independent variable.


What are the strengths and weaknesses of correlational methods of psychology?

Strengths: Correlational methods allow researchers to identify relationships between variables and make predictions, are less invasive than experimental methods, and can be used to generate hypotheses for further research. Weaknesses: Correlational studies cannot establish causal relationships between variables, are prone to third-variable problems and confounding variables, and may be limited by the quality of the measures used.


What are the four research methods?

The four main research methods are experimental research, correlational research, descriptive research, and qualitative research. Experimental research involves manipulating variables to test causal relationships, correlational research examines the relationship between variables without manipulating them, descriptive research aims to describe a phenomenon, and qualitative research explores underlying motivations, attitudes, and behaviors through methods such as interviews and observations.


What is correlational survey?

Correlational surveys involve measuring the relationship between two or more variables without manipulating them. By collecting data on these variables from a sample of participants, researchers can determine the extent to which changes in one variable are associated with changes in another, providing insight into potential patterns or connections between the variables.


This is the type of research that describes the strength and direction of relationships between variables?

Correlational


What did William Harvey use correlational design to discover?

Correlational design is a procedure where two variables are measured, without manipulation, to determine if there is a relationship. He used correlational design to describe, in detail, the systematic circulation and properties of the blood.


What are the weaknesses of using correlational research?

Correlational research cannot establish causation, only association between variables. It does not account for all potential confounding variables that could be influencing the relationship between variables. It is also susceptible to issues like selection bias and third variables impacting results.


What is correlational research method?

Correlational research method is a type of study that looks at the relationship between two or more variables in order to determine if and how they are related. It involves measuring the variables as they naturally occur without manipulating them. Correlational studies can provide valuable insights into potential relationships between variables but cannot establish causation.


Which pair of variables shows a clear causal link?

Help.


What is correlative study?

A correlational study is one where you examine correlations without manipulating any variables.


What methods is most helpful for revealing cause effect relationships A the survey b the experiment c correlational research d naturalistic observation?

The experiment method is most helpful for revealing cause-effect relationships as it involves manipulating variables to see the effect on another variable. This allows for establishing causal relationships between variables by controlling for confounding factors.