What is Association ? Explain important terms in Association.
Answers
Answer: An association defines a relationship between two entity objects based on common attributes. The relationship can be one-to-one or one-to-many; you can use two one-to-many associations to implement a many-to-many relationship. The association allows entity objects to access the data of other entity objects through a persistent reference.
Explanation:
The association is a relationship between two or more variables, such that changes in the value of one variable are associated with changes in the value of another variable. It is a fundamental concept in statistics and data analysis.
There are several important terms in association that are commonly used in statistical analysis:
Correlation: Correlation refers to the relationship between two variables and the strength and direction of the relationship. A positive correlation means that as the value of one variable increases, the value of the other variable also increases. A negative correlation means that as the value of one variable increases, the value of the other variable decreases.
Causation: Causation refers to the relationship between two variables where a change in one variable causes a change in the other variable. In other words, the change in the value of one variable directly causes a change in the value of the other variable.
Independence: Independence refers to a relationship between two variables where the value of one variable has no effect on the value of the other variable. In other words, the two variables are not associated with each other.
Confounding: Confounding occurs when a third variable is related to both of the variables in the association, making it difficult to determine the true relationship between the two variables.
In conclusion, association, correlation, causation, independence, and confounding are important terms in statistics and data analysis. Understanding these concepts can help you to analyze the relationships between variables and make more informed decisions.
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