Categories - Bland Chapter 3 - Problem 2 - Problem Set 3.1

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In summary: Hi Peter,You've asked a very good question. The abstract definition of a function $f : A \to B$ is a relation from $A$ to $B$ (i.e., a subset $R$ of $A \times B$) such that for every $a \in A$, there is a unique $b \in B$ such that $(a,b) \in R$ (and we typically write $f(a) = b$ when $(a,b) \in R$). Hence, given an object $B$ of SET and a morphism $f \in \text{Mor}(\emptyset, B)$, $f$ is viewed as a relation
  • #1
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I am reading Paul E. Bland's book, "Rings and Their Modules".

I am trying to understand Section 3.1 on Categories.

At present I am working on Problem 2 in Problem Set 3.1 and I need some help in understanding the problem and its solution.

Problem 2 (Problem Set 3.1) reads as follows:https://www.physicsforums.com/attachments/3602Now in the category Set we have:

\(\displaystyle \mathscr{O}\) is the class of all sets - that is the objects are sets

and

If \(\displaystyle A, B \in \mathscr{O} \) then \(\displaystyle \text{Mor} (A,B)\) is the set of all functions from \(\displaystyle A\) to \(\displaystyle B\) ...

Now Bland's definition of an initial and final object are as follows:https://www.physicsforums.com/attachments/3603

Now if \(\displaystyle \emptyset\) is an initial object, then \(\displaystyle \text{Mor} (\emptyset, B)\) has exactly one morphism \(\displaystyle f \ : \ \emptyset \rightarrow B\) ... ...

... ... BUT ... ... how can we have a set function emanating from a set with no elements ...

Can someone please clarify this issue/problem?

Peter
 
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  • #2
Hi Peter,

I have never rode such a strange thing, so I'm not really sure of what I'm going to say, but I think here could be an agreement.

If you consider the sets $A,B$ and the set $C=\{f:A\longrightarrow B \ : \ f \ \mbox{is an application}\}$

Then we know that in general $\#(C)=\#(B)^{\#(A)}$ and $\#(\emptyset)=0$, hence we can agree that $C_{\emptyset}=\{f:\emptyset \longrightarrow B \ : \ f \ \mbox{is an application}\}$ has one element.

A different question would be if this agreement make sense or not.
 
  • #3
Fallen Angel said:
Hi Peter,

I have never rode such a strange thing, so I'm not really sure of what I'm going to say, but I think here could be an agreement.

If you consider the sets $A,B$ and the set $C=\{f:A\longrightarrow B \ : \ f \ \mbox{is an application}\}$

Then we know that in general $\#(C)=\#(B)^{\#(A)}$ and $\#(\emptyset)=0$, hence we can agree that $C_{\emptyset}=\{f:\emptyset \longrightarrow B \ : \ f \ \mbox{is an application}\}$ has one element.

A different question would be if this agreement make sense or not.
Thanks for the help, Fallen Angel ...

Hmmm ... not sure ... still reflecting and thinking about this matter ...

Does anyone else have a viewpoint on this ... ... ?

Peter
 
  • #4
Peter said:
Thanks for the help, Fallen Angel ...

Hmmm ... not sure ... still reflecting and thinking about this matter ...

Does anyone else have a viewpoint on this ... ... ?

Peter

Hi Peter,

You've asked a very good question. The abstract definition of a function $f : A \to B$ is a relation from $A$ to $B$ (i.e., a subset $R$ of $A \times B$) such that for every $a \in A$, there is a unique $b \in B$ such that $(a,b) \in R$ (and we typically write $f(a) = b$ when $(a,b) \in R$). Hence, given an object $B$ of SET and a morphism $f \in \text{Mor}(\emptyset, B)$, $f$ is viewed as a relation from $\emptyset$ to $B$, in other words, a subset of $\emptyset \times B$. Since $\emptyset \times B = \emptyset$, $f$ is determined by the empty relation. Conversely, the empty relation gives a morphism from $\emptyset$ to $B$. Therefore, $\text{Mor}(\emptyset, B)$ has only one element. Since $B$ was an arbitrary object of SET, $\emptyset$ is the initial object of SET.
 
  • #5
Euge said:
Hi Peter,

You've asked a very good question. The abstract definition of a function $f : A \to B$ is a relation from $A$ to $B$ (i.e., a subset $R$ of $A \times B$) such that for every $a \in A$, there is a unique $b \in B$ such that $(a,b) \in R$ (and we typically write $f(a) = b$ when $(a,b) \in R$). Hence, given an object $B$ of SET and a morphism $f \in \text{Mor}(\emptyset, B)$, $f$ is viewed as a relation from $\emptyset$ to $B$, in other words, a subset of $\emptyset \times B$. Since $\emptyset \times B = \emptyset$, $f$ is determined by the empty relation. Conversely, the empty relation gives a morphism from $\emptyset$ to $B$. Therefore, $\text{Mor}(\emptyset, B)$ has only one element. Since $B$ was an arbitrary object of SET, $\emptyset$ is the initial object of SET.
Thanks for the help, Euge ...

Still reflecting on what you have written, but I get the idea, I think ...

Most helpful ... thanks again ...

Peter
 

Related to Categories - Bland Chapter 3 - Problem 2 - Problem Set 3.1

1. What is the purpose of categories in Bland Chapter 3?

The purpose of categories in Bland Chapter 3 is to organize data into groups based on common characteristics or attributes. This helps in analyzing and understanding the data more effectively.

2. How are categories different from variables?

Categories and variables are both ways of organizing data, but they serve different purposes. Categories are used to group data based on common characteristics, while variables represent the different values or attributes that can be measured or observed within a category.

3. Can categories overlap with each other?

Yes, categories can overlap with each other. For example, a category of "fruit" can overlap with a category of "red" if the fruit being discussed is a red apple. In this case, the apple would belong to both categories.

4. How do you determine the appropriate number of categories for a dataset?

The appropriate number of categories for a dataset depends on the specific data and the purpose of the analysis. Generally, it is recommended to have at least 5 categories, but the number may vary depending on the complexity of the data and the research question being addressed.

5. How can categories be used in data analysis?

Categories can be used in data analysis to compare and contrast groups, identify patterns or trends, and make predictions about the data. They can also be used to summarize and present data in a more organized and understandable way.

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