Sum principle proof: discrete mathematics

In summary, the Sum Principle is a fundamental concept in discrete mathematics that states the total number of objects in a set can be determined by adding the number of objects in each of its subsets. This principle is often used in combinatorics and probability to calculate the number of possible outcomes or combinations. The proof of the Sum Principle relies on the concept of counting, where the total number of objects is represented by a sum of smaller subsets. This allows for a more efficient and systematic approach to calculating the number of objects in a set. The Sum Principle is an essential tool for solving problems in various fields, from computer science to economics, and helps to simplify complex calculations.
  • #1
member 587159
Theorem: Let ##A_1, A_2, ..., A_k## be finite, disjunct sets. Then ##|A_1 \cup A_2 \cup \dots \cup A_k| = |A_1| + |A_2| + \dots + |A_k|##

I will give the proof my book provides, I don't understand several parts of it.

Proof:

We have bijections ##f_i: [n_i] \rightarrow A_i## for ##i \in [k]##

Notice: ##[\sum\limits_{i=1}^{k}n_i] = [1..n_1]\cup[(n_1 + 1)..(n_1 + n_2)]\cup\dots\cup[(\sum\limits_{i=1}^{k-1} n_i)+ 1 ..\sum\limits_{i=1}^{k}n_i]##

Define:

##f: [\sum\limits_{i=1}^{k}n_i] \rightarrow A_1 \cup A_2 \cup \dots \cup A_k##

by

##f(i) = f_j(i - \sum\limits_{i=1}^{j-1}n_i)## if ##i \in [(\sum\limits_{l=1}^{j-1}n_l) + 1.. \sum\limits_{l=1}^{j}n_l]##

Verify yourself that f is a bijection. Don't forget that the sets are disjunct. QED.

I know that the notation [n] = [1..n] = {1,2,3, ...} means and also ##[n_1..n_2]## = {##n_1, n_1 +1, ... n_2##}

Questions

1) What does the notation ##f_i: [n_i] \rightarrow A_i## for ##i \in [k]## mean? Does it mean that if f is a bijection, then ##A_i## has ##n_i## elements?
2) Where does the ##j## in ##f(i) = f_j(i - \sum\limits_{i=1}^{j-1}n_i)## if ##i \in [(\sum\limits_{l=1}^{j-1}n_l) + 1.. \sum\limits_{l=1}^{j}n_l]## come from? What are the restrictions on j? j can't be a random number right?

Thanks in advance.
 
Mathematics news on Phys.org
  • #2
Math_QED said:
1) What does the notation ##f_i: [n_i] \rightarrow A_i## for ##i \in [k]## mean? Does it mean that if f is a bijection, then ##A_i## has ##n_i## elements?
It means that ##f_i## is a function whose domain is the set ##\{1,2,...,n_i\}## and range is ##A_i##. I haven't seen the notation ##[n_i]## before but it can be inferred from the context what it means and I like it.

The part to which your second question refers is written wrongly. I've got to rush off now but I'll explain why when I get back if somebody else has not already done so.
 
  • Like
Likes member 587159
  • #3
This is perhaps a case where it's obvious what the proof is doing but the notation gets messy. My suggestion is to try to work out the strategy of the proof for yourself and then map that strategy back to the proof you are given.

For example, you could label the elements of these sets:

##A_1 = \{ a_1, \dots , a_{n_1} \} ##

etc.

I wonder whether the proof given stands up if some of the sets can be empty?
 
  • Like
Likes member 587159
  • #4
PeroK said:
This is perhaps a case where it's obvious what the proof is doing but the notation gets messy. My suggestion is to try to work out the strategy of the proof for yourself and then map that strategy back to the proof you are given.

For example, you could label the elements of these sets:

##A_1 = \{ a_1, \dots , a_{n_1} \} ##

etc.

I wonder whether the proof given stands up if some of the sets can be empty?

But do you have any idea what the j could stand for though? And you are right, I should think about what happens when some sets are empty but first I need to understand the proof. Thanks for your answer.
 
  • #5
Math_QED said:
But do you have any idea what the j could stand for though? And you are right, I should think about what happens when some sets are empty but first I need to understand the proof. Thanks for your answer.
You may write ##f=(f_1, \dots , f_k)## where ##f(i+\sum_{m=1}^{m=j-1}n_m):=f_j(i)## iff ##i \in [n_j]##. It is all about extending all the ##f_j## to a function ##f##.
##f(i)=f_1(i)## for ##1 \leq i \leq n_1##
##f(i)=f_2(i-n_1)## for ##n_1+1 \leq i \leq n_1+n_2##
##f(i)=f_3(i-n_1-n_2)## for ##n_1+n_2+1 \leq i \leq n_1+n_2+n_3##
etc.
The index ##j## is needed to distinguish the different components of ##f##.
(However I haven't checked the formula you typed and what Andrew refers to.)

Edit: corrected a formula, and I like the notation [n_j], too.
 
  • Like
Likes member 587159
  • #6
Math_QED said:
But do you have any idea what the j could stand for though? And you are right, I should think about what happens when some sets are empty but first I need to understand the proof. Thanks for your answer.
The proof is just trying to select the jth set that ##i## belongs to.

It seems to me it's easier just listing the elements of the union.

Also, like Andrew, I inferred the meaning of the notation by working out what the proof was trying to do.

The same with what ##j## is. I worked backwards from what the proof must be trying to do.

I think it should be something like:

where sum of the n's to ##j-1 < i \le## sum of the n's to ##j##
 
  • Like
Likes member 587159
  • #7
Thanks all, those answers helped a lot.
 
  • #8
Just to be sure, ##j \leq k## is always true here? And the j is there to indicate the set ##A_j## ?
 
  • #9
Math_QED said:
Just to be sure, ##j \leq k## is always true here? And the j is there to indicate the set ##A_j## ?
Yes. And the ##f_j \; : \; [n_j] \rightarrow A_j##.
 
  • Like
Likes member 587159

1. What is the sum principle in discrete mathematics?

The sum principle, also known as the addition principle, states that when counting the number of ways to choose or arrange elements from two or more sets, the total number of possibilities is equal to the sum of the individual sets' sizes.

2. How is the sum principle used in discrete mathematics?

The sum principle is used to solve problems involving counting and combinations. It helps to determine the total number of possible outcomes when dealing with multiple sets or choices.

3. Can you provide an example of a sum principle proof?

For example, if there are 3 types of fruits (apples, bananas, and oranges) and 2 types of toppings (chocolate and caramel), the sum principle can be used to calculate the total number of possible fruit and topping combinations. In this case, it would be 3 + 2 = 5 possible combinations.

4. Are there any exceptions to the sum principle?

Yes, there are exceptions to the sum principle, such as when counting overlapping or repeated elements. In these cases, the principle of inclusion and exclusion is used instead to avoid overcounting.

5. How does the sum principle relate to other principles in discrete mathematics?

The sum principle is closely related to the product principle, which states that the total number of ways to perform a sequence of tasks is equal to the product of the number of choices at each step. Both principles are fundamental in combinatorics and are often used in conjunction to solve more complex counting problems.

Similar threads

Replies
3
Views
800
  • Advanced Physics Homework Help
Replies
1
Views
742
Replies
11
Views
1K
  • General Math
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
727
Replies
1
Views
2K
  • Calculus and Beyond Homework Help
Replies
1
Views
495
  • Calculus and Beyond Homework Help
Replies
5
Views
525
  • Set Theory, Logic, Probability, Statistics
Replies
19
Views
2K
Back
Top