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What are the three conditions necessary for causation between variables?

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∙ 14y ago

Updated: 4/30/2024

correlation, temporal priority, lack of spurious correlation

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The three conditions necessary for causation between variables are covariance (relationship between variables), temporal precedence (the cause must precede the effect in time), and elimination of plausible alternative explanations (other possible causes are ruled out).

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When two variables are related but one does not cause the other researchers term the situation?

Researchers term the situation as correlation. Correlation indicates a statistical relationship between two variables, showing how they move together but not necessarily implying causation. The strength and direction of the correlation can provide insights into the relationship between the variables.

What is experimentation in sociology?

Experimentation in sociology involves designing and conducting studies to determine causation or relationships between variables in a controlled setting. Researchers manipulate one or more variables to observe their effects on others in order to test hypotheses and theories. This method allows sociologists to gather empirical evidence to understand social phenomena and human behavior.

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.

What is a casual relationship in research?

A casual relationship in research refers to a situation where a change in one variable appears to cause a change in another variable. It implies that there is a cause-and-effect link between the two variables. However, it is important to remember that correlation does not imply causation, and establishing a causal relationship requires further rigorous testing and evidence.

What is a popular form of summary many sociologists utilize to quickly and clearly show a relationship between two variables?

Sociologists often use scatter plots to visually represent the relationship between two variables. This graphical tool helps quickly identify patterns and trends in the data, showing the strength and direction of the relationship between the variables.

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Related Questions

What are some relationships that exist between variables?

Causation, correlation...

What is the study of causation called?

The study of causation is called causality or causation theory. It involves examining the cause-and-effect relationships between variables or events to understand how one factor influences another.

What is the difference between causation and correlation in statistical analysis?

Causation in statistical analysis refers to a direct cause-and-effect relationship between two variables, where changes in one variable directly cause changes in the other. Correlation, on the other hand, simply indicates a relationship between two variables without implying causation. In other words, correlation shows that two variables tend to change together, but it does not prove that one variable causes the other to change.

In what ways does correlation differ from causation?

Correlation is a statistical relationship between two variables, while causation implies that one variable directly influences the other. Just because two variables are correlated does not mean that one causes the other.

What is the difference between causation and correlation?

Causation refers to a direct cause-and-effect relationship between two variables, where one variable directly influences the other. Correlation, on the other hand, refers to a relationship between two variables where they tend to change together, but one variable may not necessarily cause the change in the other.

Can you explain the difference between causation and correlation?

Causation refers to a direct cause-and-effect relationship between two variables, where one variable directly influences the other. Correlation, on the other hand, refers to a relationship between two variables where they tend to change together, but one variable may not necessarily cause the change in the other.

What's the difference between causation and correlation?

Causation refers to a direct cause-and-effect relationship between two variables, where one variable directly influences the other. Correlation, on the other hand, refers to a relationship between two variables where they tend to change together, but one variable may not necessarily cause the change in the other.

What is the relationship between correlation and causation?

Correlation is a statistical relationship between two variables, while causation implies that one variable directly influences the other. Correlation does not prove causation, as there may be other factors at play. It is important to consider other evidence before concluding a causal relationship.

Can you explain the difference between correlation and causation?

Correlation is a relationship between two variables where they change together, but it doesn't mean one causes the other. Causation, on the other hand, implies that one variable directly causes a change in the other.

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 the distinction between correlation and causation?

Correlation is a relationship between two variables where they change together, but it does not mean that one causes the other. Causation, on the other hand, implies that one variable directly influences the other. In simpler terms, correlation shows a connection, while causation shows a cause-and-effect relationship.

Is causation the focus of explanatory research?

Yes, causation is a central focus of explanatory research. Explanatory research aims to understand the relationships between variables and uncover the causes behind certain phenomena or outcomes. It seeks to explain why certain events occur and how variables are connected to each other.

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