Example for which the relation does not stand

In summary, the conversation discusses the relationship between sets and relations, specifically the statement that $R[A \cap B] \subset R[A] \cap R[B]$. It is proven using a logical argument, but it is also acknowledged that the reverse statement, $R[A] \cap R[B] \subset R[A \cap B]$, may not always hold true depending on the function $R$. An example is given to illustrate this.
  • #1
evinda
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Hello! (Smile)
It stands that $R[A \cap B] \subset R[A] \cap R$, since:

$$y \in R[A \cap B] \rightarrow \exists x \in A \cap B: xRy \rightarrow \exists x(x \in A \wedge xRy) \wedge (x \in B: xRy) \rightarrow y \in R[A] \wedge x \in R \rightarrow y \in R[A] \cap R$$

But, it doesn't stand, that: $R[A] \cap R \subset R[A \cap B]$. Could you give me an example, for which the last relation does not stand? (Thinking)
 
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  • #2
Let $R$ be a non-injective function so that $R(x_1)=R(x_2)$ where $x_1\ne x_2$. Take $A=\{x_1\}$ and $B=\{x_2\}$.
 

FAQ: Example for which the relation does not stand

What is an example of a relation that does not stand?

An example of a relation that does not stand is the relation between height and intelligence. While some may believe that taller people are inherently more intelligent, there is no scientific evidence to support this claim.

How do you determine if a relation stands or not?

A relation stands if there is a consistent and significant correlation between the two variables being studied. This means that as one variable changes, the other also changes in a predictable manner.

Can a relation that does not stand be considered a causal relationship?

No, a relation that does not stand cannot be considered a causal relationship. A causal relationship requires a strong and direct link between the two variables, whereas a relation that does not stand only shows a weak or non-existent correlation.

What are some factors that can cause a relation to not stand?

There are many factors that can contribute to a relation not standing, such as confounding variables, bias in data collection, or a small sample size. It is important to thoroughly analyze all possible factors before concluding that a relation does not stand.

Why is it important to identify relations that do not stand?

Identifying relations that do not stand is crucial in order to avoid making false assumptions or drawing incorrect conclusions. It also helps to guide further research and understanding of the true nature of the relationship between the variables being studied.

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