Question about proof from a guy with a highschool education

  • #701
Suppose the set ##\{ A,B,C,D,E \}##.I want to find the number of lenght-5 lists made from this set that have at least one letter repeated.

My guess is I need to calculate the total amount and substract the amount of lists using all different letters from it.

##5(5)(5)(5)(5) - 5(4)(3)(2)(1)## , ##3125 - 120 = 3005## lists with at least one letter repeated.

any thoughts on that?

thank you!
 
Last edited:
Mathematics news on Phys.org
  • #702
That sounds good too. But you should post textbook-style problems in the homework forums.
 
  • #703
I'm back :biggrin:

Vacation for 2 weeks !
 
Last edited:
  • #704
Picking up where I left off:

Since we are asked to count none-repetitive lists so many times , we can use factorials to handle the counting.

If I understood factorials correctly (in relation to this counting list concept) , ##n!## gives us the total amount of possible none-repetitive lists created from ##n## number of elements.

So both ##0!## and ##1!## should give us 1 list because of the empty list for ##0!##.

The book of proof introduces the following generalized formula: ##n! = n \cdot (n-1)!##

The formula works but I wonder how useful it is once there's a lot of elements.If you don't know what ##(n-1)!## is you are condemned to repeat the formula until you know what it is.

(post in progress...)

Since the length ##k## of lists isn't always the same , they introduce the formula ##n(n-1)(n-2) \cdots (n-k+1)## to find the number of none-repetitive lists of length ##k## given ##n## symbols or elements.

So if ##n=5## and you want to create none-repetitive length 3 lists , you can do ##5 \cdot 4 \cdot 3## and you stop there because of ##(n-k+1)## being ##(5-3+1) = 3## so the answer is ##5 \cdot 4 \cdot 3 = 60##.So there's 60 non-repetitive lists of length 3 if you use 5 elements.

Just after that they introduce something I'm a little bit confused about at first glance.

Following their introduction of the formula ##n(n-1)(n-2) \cdots (n-k+1).## , they state:

Notice that by cancellation this value can also be written as

##\frac{n(n-1)(n-2) \ \cdots \ (n-k+1)(n-k)(n-k-1) \ \cdots \ 3 \cdot 2 \cdot 1}{(n-k)(n-k-1) \ \cdots \ 3 \cdot 2 \cdot 1} = \frac{n!}{(n-k)!}##

My confusion is probably related to the notation.

From my example:

##\frac{5 \cdot 4 \cdot 3 \cdot 2 \cdot 1}{2 \cdot 1}= \frac{5!}{2!}=\frac{120}{2}=60##

The part I'm confused about is the ##(n-k-1) \cdots 3 \cdot 2 \cdot 1## in:

##\frac{n(n-1)(n-2) \ \cdots \ (n-k+1)(n-k)(n-k-1) \ \cdots \ 3 \cdot 2 \cdot 1}{(n-k)(n-k-1) \ \cdots \ 3 \cdot 2 \cdot 1} = \frac{n!}{(n-k)!}##

The ##3 \cdot 2 \cdot 1## at the end , does it mean that you continue in the ##(n-k)(n-k-1)## multiplication sequence until ##(n-k-1)=1## or ##(n-k)=1## or ##(n-k-x)=1## with ##x \in \mathbb{N}## and then you stop?

I ask because if you use 4 elements and a lenght-3 list , ##(n-k-1)## is ##(4-3-1)=0## and then you end up with ##\frac{0}{0}##.So in this example , it would mean that you have to stop at ##(n-k)## which is ##(4-3)=1## is that correct?

thank you!
 
Last edited:
  • #705
reenmachine said:
If I understood factorials correctly (in relation to this counting list concept) , ##n!## gives us the total amount of possible none-repetitive lists created from ##n## number of elements.
Right, because there are n ways to pick the first entry, n-1 ways to pick the second one, and so on.

reenmachine said:
The book of proof introduces the following generalized formula: ##n! = n \cdot (n-1)!##

The formula works but I wonder how useful it is once there's a lot of elements.If you don't know what ##(n-1)!## is you are condemned to repeat the formula until you know what it is.
It's especially useful when there's a lot of elements. Suppose that you want to prove that a statement P(n) is true for all non-negative integers n. You obviously can't do this one statement at a time: P(0), P(1), ... What you do instead is to prove the following two statements:

P(0)
For all non-negative integers n, if P(n) then P(n+1).

If P(n) is a statement that involves n!, you will find the formula (n+1)!=(n+1)n! extremely useful when you need to prove the second statement above.

But the formula isn't introduced just to be useful in proofs and calculations. It gives us a way to unambiguously state the definition of n! for all ##n\in\mathbb N##. First we define 0! by ##0!=1##, and then, for each ##n\in\mathbb Z^+##, we define ##n!## by ##n!=n(n-1)!##.

Edit: I see now that the book "defines" n! as the number of non-repetitive lists that can be made from n symbols. I don't like that definition. The one I just stated is standard, and simpler.

reenmachine said:
So if ##n=5## and you want to create none-repetitive length 3 lists , you can do ##5 \cdot 4 \cdot 3## and you stop there because of ##(n-k+1)## being ##(5-3+1) = 3## so the answer is ##5 \cdot 4 \cdot 3 = 60##.So there's 60 non-repetitive lists of length 3 if you use 5 elements.
5 ways to choose the first element, 4 ways to choose the second, 3 ways to choose the third. So 5·4·3=60.

reenmachine said:
Just after that they introduce something I'm a little bit confused about at first glance.

Following their introduction of the formula ##n(n-1)(n-2) \cdots (n-k+1).## , they state:
For example,
$$5\cdot 4\cdot 3=\frac{5\cdot 4\cdot 3\cdot 2\cdot 1}{2\cdot 1}=\frac{5!}{2!}.$$ With n=5 and k=3,
$$5\cdot 4\cdot 3=n(n-1)(n-2) =n\cdots(n-k+1) =\frac{n\cdots(n-k+1)(n-k)\cdots 1}{(n-k)\cdots 1} =\frac{n!}{(n-k)!} =\frac{5!}{2!}.$$
reenmachine said:
My confusion is probably related to the notation.

From my example:

##\frac{5 \cdot 4 \cdot 3 \cdot 2 \cdot 1}{2 \cdot 1}= \frac{5!}{2!}=\frac{120}{2}=60##

The part I'm confused about is the ##(n-k-1) \cdots 3 \cdot 2 \cdot 1## in:
The ##3 \cdot 2 \cdot 1## at the end , does it mean that you continue in the ##(n-k)(n-k-1)## multiplication sequence until ##(n-k-1)=1## or ##(n-k)=1## or ##(n-k-x)=1## with ##x \in \mathbb{N}## and then you stop?

I ask because if you use 4 elements and a lenght-3 list , ##(n-k-1)## is ##(4-3-1)=0## and then you end up with ##\frac{0}{0}##.So in this example , it would mean that you have to stop at ##(n-k)## which is ##(4-3)=1## is that correct?
Yes, the notation looks weird when n-k-1 ≤ 3. Since the numerator looks like a product of at least nine factors, it's also weird if n<9. This is a problem with the notation, but I think it's pretty common to ignore that and use a notation that only makes sense for certain values of n and k.

I think that now that you know that the notation isn't supposed to make sense, it will make perfect sense. :smile:
 
Last edited:
  • #706
Fredrik said:
It's especially useful when there's a lot of elements. Suppose that you want to prove that a statement P(n) is true for all positive integers n. You obviously can't do this one statement at a time: P(0), P(1), ... What you do instead is to prove the following two statements:

First of all , just so it's completely clear , here the notations means: P(n) = statement about n?

P(0)
For all positive integers n, if P(n) then P(n+1).

I'm not sure I understand what P(0) is doing there.Just so we're clear again , did you mean that you first have to prove P(0) , and then you have to prove that for all positive integers n , ##P(n) \rightarrow P(n+1)## , proving that if P(0) is true , then P(1) is true , which implies that P(2) is true and on and on...? I'm confused by this because 0 isn't a positive integer as far as I know?!?

If P(n) is a statement that involves n!, you will find the formula (n+1)!=(n+1)n! extremely useful when you need to prove the second statement above.

So the formula is extremely useful to connect a statement about a specific number to another larger set of numbers? What I meant in my original post was that the formula wasn't very useful to find what ##n!## is if ##n## is a large integer.

But the formula isn't introduced just to be useful in proofs and calculations. It gives us a way to unambiguously state the definition of n! for all ##n\in\mathbb N##. First we define ##0!=0##, and then, for each ##n\in\mathbb Z^+##, we define ##n!## by ##n!=n(n-1)!##.

What do you mean by we define ##0!=0##?

For example,
$$5\cdot 4\cdot 3=\frac{5\cdot 4\cdot 3\cdot 2\cdot 1}{2\cdot 1}=\frac{5!}{2!}.$$ With n=5 and k=3,
$$5\cdot 4\cdot 3=n(n-1)(n-2) =n\cdots(n-k+1) =\frac{n\cdots(n-k+1)(n-k)\cdots 1}{(n-k)\cdots 1} =\frac{n!}{(n-k)!} =\frac{5!}{2!}.$$

Yeah it's much clearer that way.

Yes, the notation looks weird when n-k-1 ≤ 3. Since the numerator looks like a product of at least nine factors, it's also weird if n<9. This is a problem with the notation, but I think it's pretty common to ignore that and use a notation that only makes sense for certain values of n and k.

I think that now that you know that the notation isn't supposed to make sense, it will make perfect sense. :smile:

Pretty sure I get it now :smile:

Basically they gave us this notation as an example of what to do if you're dealing with larger numbers.

thank you Fredrik!

I'm glad to be back!
 
Last edited:
  • #707
reenmachine said:
First of all , just so it's completely clear , here the notations means: P(n) = statement about n?
Yes.

reenmachine said:
What do you mean by we define ##0!=0##?
D'oh. Typo. I meant to say that we define 0! by 0!=1.

reenmachine said:
I'm not sure I understand what P(0) is doing there.Just so we're clear again , did you mean that you first have to prove P(0) , and then you have to prove that for all positive integers n , ##P(n) \rightarrow P(n+1)## , proving that if P(0) is true , then P(1) is true , which implies that P(2) is true and on and on...? I'm confused by this because 0 isn't a positive integer as far as I know?!?
OK, I see I got more details wrong in my statement. I will edit it above, and include a new explanation below. It looks like you got the general idea anyway.

I include 0 in ##\mathbb N##, and use the notation ##\mathbb Z^+## for the positive integers. I should have mentioned that, since the book uses the notation ##\mathbb N## for the positive integers.

The proof technique I'm talking about is called "induction". It's chapter 10 in Book of proof. The idea is that you can prove ##\forall n\in\mathbb N~P(n)## by proving the two statements ##P(0)## and ##\forall n\in\mathbb N~P(n)\to P(n+1)##. This is useful when you're unable to prove ##P(n)## for an arbitrary ##n\in\mathbb N##.

Similarly, you can prove ##\forall n\in\mathbb Z^+~P(n)## by proving the two statements ##P(1)## and ##\forall n\in\mathbb Z^+~P(n)\to P(n+1)##.

reenmachine said:
So the formula is extremely useful to connect a statement about a specific number to another larger set of numbers? What I meant in my original post was that the formula wasn't very useful to find what ##n!## is if ##n## is a large integer.
I would say that since it's part of the definition of n! (the other part is the statement 0!=1), the formula is always useful. I mentioned induction because when you prove that P(n) implies P(n+1), you would typically only have to use the formula once. (This is of course assuming that P(n) is, for all n, a statement that involves n!).
 
  • #708
Fredrik said:
OK, I see I got more details wrong in my statement. I will edit it above, and include a new explanation below. It looks like you got the general idea anyway.

I include 0 in ##\mathbb N##, and use the notation ##\mathbb Z^+## for the positive integers. I should have mentioned that, since the book uses the notation ##\mathbb N## for the positive integers.

The proof technique I'm talking about is called "induction". It's chapter 10 in Book of proof. The idea is that you can prove ##\forall n\in\mathbb N~P(n)## by proving the two statements ##P(0)## and ##\forall n\in\mathbb N~P(n)\to P(n+1)##. This is useful when you're unable to prove ##P(n)## for an arbitrary ##n\in\mathbb N##.

Similarly, you can prove ##\forall n\in\mathbb Z^+~P(n)## by proving the two statements ##P(1)## and ##\forall n\in\mathbb Z^+~P(n)\to P(n+1)##.

Yeah this is what I had in mind , thank you!

I would say that since it's part of the definition of n! (the other part is the statement 0!=1), the formula is always useful. I mentioned induction because when you prove that P(n) implies P(n+1), you would typically only have to use the formula once. (This is of course assuming that P(n) is, for all n, a statement that involves n!).

Very clear again thanks!
 
  • #709
Counting subset

They introduce a weird notation that ressemble a fraction but without the horizontal line in the middle.I won't use it unfortunately because I don't know how to write it in LaTeX.

Anyway they use it to introduce a new formula to find the number of possible subsets created from a sets with ##n## number of elements and choosing ##k## number of elements from it.

They illustrate the formula using the set ##\{a,b,c,d,e\}## and taking 3 elements from it , which would give us 10 subsets possible.Then they tell us to use each subsets (containing 3 elements each) and to verify how many none-repetitive lists you could produce from these 3 elements.The answer is obviously 3!= 6 , and with this we can also do ##6 \cdot 10## to know how many lenght-3 none-repetitive list we can produce with the entire earlier set ##\{a,b,c,d,e\}##.This is the same as ##\frac{5!}{(5-3)!}## and the answer is 60.With this you can use the formula ##\frac{n!}{k!(n-k)!}## to find the number of possible subsets created from a set with ##n## number of elements and choosing ##k## number of elements from it.It works because you divided (from our exemple) 3! from both ##\frac{5!}{(5-3)!}## and ##3! \cdot 10##.

This is all simple enough , but I would like to clarify one thing:

Suppose you have: ##\frac{7!}{2!(7-2)!} = \frac{7!}{2!5!}##.

Does it matter which factorial you choose to cancel in the denominator?

Exemple: ##\frac{7 \cdot 6 \cdot 5!}{2!5!} = \frac{7 \cdot 6}{2!} = \frac{7 \cdot 6 \cdot 5 \cdot 4 \cdot 3 \cdot 2!}{2!5!} = \frac{7 \cdot 6 \cdot 5 \cdot 4 \cdot 3}{5!}##.

I've done the calculations and it seems correct.

I know this is very trivial but I like to always see clearly in my computations.Basically I'm not sure if I have any real question in this post as I kind of thought it out while I was typing so sorry about that :-p
 
  • #710
reenmachine said:
Counting subset

They introduce a weird notation that ressemble a fraction but without the horizontal line in the middle.I won't use it unfortunately because I don't know how to write it in LaTeX.

That is called a "binomial coefficient". The LaTeX code is

Code:
\binom{n}{k}

For ##\binom{n}{k}##.

Does it matter which factorial you choose to cancel in the denominator?

No, it doesn't matter.
 
  • #711
micromass said:
That is called a "binomial coefficient". The LaTeX code is

Code:
\binom{n}{k}

For ##\binom{n}{k}##.



No, it doesn't matter.

Thank you! Very appreciated!
 
  • #712
reenmachine said:
Does it matter which factorial you choose to cancel in the denominator?
Since a cancellation doesn't change the value of the fraction, it doesn't matter what you cancel (as long as it's not zero).
 
  • #713
What do you guys think I should do when I'm facing exercises which are using a concept Y I don't know anything about to verify my knowledge of a different concept X that is taught in the book?

Should I just skip them? This is a little bit frustrating sometimes but it's something I have to accept since I decided to learn some mathematics that are ahead of where I officially am academically.
 
Last edited:
  • #714
The book of proof introduces the pattern ##\binom{n+1}{k} = \binom{n}{k-1} + \binom{n}{k}## for any integers ##n## and ##k## with ##0<k≤n##.

Then they say that the set ##A= \{0,1,2,3, \cdots , n\}## has n+1 elements (because of 0?).So ##\binom{n+1}{k}## equals the number of ##k## elements subsets of ##A##.Then they say that the subsets can be divided into two categories , those with 0 and those without 0.This is where I'm a little bit confused.They say that ##\binom{n}{k-1}## equals the number of ##k## elements subsets of A that contains 0.I can compute it , but I'm not sure I get it yet.

When ##k## becomes ##k-1## , is it because you already know that 0 will be one element selected from A? So basically you do ##\binom{n}{k-1}## to find the amount of possible combinations of ##k-1## elements that can be connected to 0 as a subset , and since it's not repetitive , you transform ##n+1## into ##n## because 0 is already taken?

Coming back to ##\binom{n+1}{k} = \binom{n}{k-1} + \binom{n}{k}## , then ##\binom{n}{k}## is just the subsets without 0 which you add to your amount of subsets with 0 , all of this to obtain the number of subsets taking ##k##-elements from a set with ##n+1## elements?

As for the "big picture" of this pattern , was the intuition here simply to "isolate" the consequences on the number of subsets (created by ##+1## in ##n+1##) with ##\binom{n}{k-1}##?

After that they illustrate it using some kind pascal triangle with a bunch of binomial coefficient instead of integers.From what I saw this meant that the addition of two binomial coefficients placed side by side in the triangle results in the binomial coefficient placed under both.

edit: Just saw that the results of the binomial coefficients are placed at the same spot as pascal's triangle integers in the triangle and they are equal.Is this why the pascal triangle was created in the first place?

thank you!
 
Last edited:
  • #715
Hey, I'll try to answer some of your concerns.

reenmachine said:
The book of proof introduces the pattern ##\binom{n+1}{k} = \binom{n}{k-1} + \binom{n}{k}## for any integers ##n## and ##k## with ##0<k≤n##.

Then they say that the set ##A= \{0,1,2,3, \cdots , n\}## has n+1 elements (because of 0?)

Yep, it's because 0 is also an element of that set.

So ##\binom{n+1}{k}## equals the number of ##k## elements subsets of ##A##.

That's right, it is the number of subsets of A that have a cardinality of k.

The way I think about it as this (if you don't know this, these binomial coefficients are read "n choose k" so what I'm about to say is obvious)

##\binom{n+1}{k}##

is the number of ways I can select k elements from n+1 elements. For example, if we have the set {a,b} and I want to choose 2 elements, there's only one choice, to pick a, and b. So 2 choose 2, or the binomial coefficient ##\binom{2}{2}## is 1, and in fact ##\binom{n}{n}## is 1.

This also provides a very intuitive understanding for
##\binom{n}{k} = \binom{n}{n-k}##

Because there is no difference between choosing to "take" k elements and choosing to "leave" n-k elements, so the number of ways to choose k or n-k elements must be the same (sorry if this was covered already.)

You can choose to think of it as the "number of subsets" if you like, but in dealing with probability or applications, it is helpful for me to think of it in the terms of number of ways that something can happen.

For example, the number of possible poker hands is ##\binom{52}{5}##, because there are 52 cards and a poker hand consists of 5 cards. So when you get a hand of poker, you got one of the possible subsets of the 52 cards that is 5 cards large.



Then they say that the subsets can be divided into two categories , those with 0 and those without 0.This is where I'm a little bit confused.They say that ##\binom{n}{k-1}## equals the number of ##k## elements subsets of A that contains 0.I can compute it , but I'm not sure I get it yet.

When ##k## becomes ##k-1## , is it because you already know that 0 will be one element selected from A? So basically you do ##\binom{n}{k-1}## to find the amount of possible combinations of ##k-1## elements that can be connected to 0 as a subset , and since it's not repetitive , you transform ##n+1## into ##n## because 0 is already taken?

That's exactly right. 0 is kind of "put on reserve." The number of subsets that have a cardinality of k and contain 0, means that I am saying "0 is here, now pick the remaining k-1 elements of this set." The number of ways to pick the remaining elements is then ##\binom{n}{k-1}## , and that is the number of subsets that contain 0. You designated one of the elements as 0, then you select k-1 more elements, giving you a set of k elements.


Coming back to ##\binom{n+1}{k} = \binom{n}{k-1} + \binom{n}{k}## , then ##\binom{n}{k}## is just the subsets without 0 which you add to your amount of subsets with 0 , all of this to obtain the number of subsets taking ##k##-elements from a set with ##n+1## elements?

Pretty much.

##\binom{n}{k-1}## means "the number of ways to pick k-1 elements from n elements." We are only picking k-1 elements because the 0 is already in every set we are considering, and it can't appear twice.

##\binom{n}{k}## means "the number of ways to pick k elements from n elements." So the n elements being considered here are the nonzero elements only. That is where our choices can be made, because every single set that contains 0 is already accounted for in the first binomial coefficient.



As for the "big picture" of this pattern , was the intuition here simply to "isolate" the consequences on the number of subsets (created by ##+1## in ##n+1##) with ##\binom{n}{k-1}##?

thank you!

If I understand you correctly, I think that is a fitting interpretation.
 
  • #716
1MileCrash said:
Hey, I'll try to answer some of your concerns.

Thank you for your help!

Yep, it's because 0 is also an element of that set.

Yeah as I wrote the rest of the post it became pretty clear but I didn't edit it.

This also provides a very intuitive understanding for
##\binom{n}{k} = \binom{n}{n-k}##

Because there is no difference between choosing to "take" k elements and choosing to "leave" n-k elements, so the number of ways to choose k or n-k elements must be the same (sorry if this was covered already.)

Very clear! Another way to put it would be: ##\binom{n}{k} = \frac{n!}{k!(n-k)!} = \binom{n}{n-k} = \frac{n!}{(n-k)!(n-(n-k))!}## is that correct? Since ##(n-(n-k)) = k## , we have ##k!(n-k)! = (n-k)!k!##.

For example, the number of possible poker hands is ##\binom{52}{5}##, because there are 52 cards and a poker hand consists of 5 cards. So when you get a hand of poker, you got one of the possible subsets of the 52 cards that is 5 cards large.

Nice exemple.But good lord , some people still play 5-card draw poker? :smile:

That's exactly right. 0 is kind of "put on reserve." The number of subsets that have a cardinality of k and contain 0, means that I am saying "0 is here, now pick the remaining k-1 elements of this set." The number of ways to pick the remaining elements is then ##\binom{n}{k-1}## , and that is the number of subsets that contain 0. You designated one of the elements as 0, then you select k-1 more elements, giving you a set of k elements.

Very clear!

Thanks a lot for taking the time to help me!
 
Last edited:
  • #717
reenmachine said:
Very clear! Another way to put it would be: ##\binom{n}{k} = \frac{n!}{k!(n-k)!} = \binom{n}{n-k} = \frac{n!}{(n-k)!(n-(n-k))!}## is that correct? Since ##(n-(n-k)) = k## , we have ##k!(n-k)! = (n-k)!k!##.

Yes, when you let the choice be n-k instead of k, you can quickly see that the only thing that happens is that the multiplication in the denominator flips.

It's one of those cool things in math where we intuitively believe something about a physical thing (that choosing to "take" n donuts from a box and choosing to "leave" n-k donuts from a box are really the same thing) and our little algebra symbols readily agree. :cool:
 
  • #718
reenmachine said:
The book of proof introduces the pattern ##\binom{n+1}{k} = \binom{n}{k-1} + \binom{n}{k}## for any integers ##n## and ##k## with ##0<k≤n##.

This is known as Pascal's rule. See also Pascal's triangle.
 
  • #719
I randomly ended up in this thread : https://www.physicsforums.com/showthread.php?p=4450910#post4450910 and thought it was interesting since I'm currently working on this.

I'm having some problems understanding what (a) is in that thread and if ##n## is assumed to be a positive integer right off the bat?

In trying to prove P(0) , I attempted:

We will attempt to prove that ##\binom{n}{k}## is an integer if ##k=0##.

We know ##\binom{n}{k}## is equal to ##\frac{n!}{k!(n-k)!}##.If ##k=0## , then we have ##\frac{n!}{0!(n-0)!}##.Since 0!=1 , we have ##\frac{n!}{1 \cdot n!} = \frac{n!}{n!} = 1##.

what are your thoughts on this? I'm still having trouble deciding what I can assume and what I have to prove.Do I have to prove that 0!=1?

(I understand I didn't prove the second part , just verifying with the first step , it's been a while since I wrote a proof.)

thank you!
 
  • #720
reenmachine said:
I randomly ended up in this thread : https://www.physicsforums.com/showthread.php?p=4450910#post4450910 and thought it was interesting since I'm currently working on this.

I'm having some problems understanding what (a) is in that thread and if ##n## is assumed to be a positive integer right off the bat?

In trying to prove P(0) , I attempted:

We will attempt to prove that ##\binom{n}{k}## is a positive integer if ##k=0##.

We know ##\binom{n}{k}## is equal to ##\frac{n!}{k!(n-k)!}##.If ##k=0## , then we have ##\frac{n!}{0!(n-0)!}##.Since 0!=1 , we have ##\frac{n!}{1 \cdot n!} = \frac{n!}{n!} = 1##.

what are your thoughts on this?

Seems good.

I'm still having trouble deciding what I can assume and what I have to prove.Do I have to prove that 0!=1?

Depends on your definition of factorial. Most definitions will take ##0! = 1## into the definition, so you won't need to prove it.
 
  • #721
woops , blunder
 
Last edited:
  • #722
n is assumed to be a nonnegative integer right off the bat because n! is only defined for those numbers.

Also, this proof comes into play with what we discussed earlier.

We already discussed why (n choose n) is 1.

And, you've shown already that (n choose k) = (n choose (n-k)) right? So what happens if k=0?

What you did proves it, I am just showing another way to look at it.
 
Last edited:
  • #723
1MileCrash said:
n is assumed to be a nonnegative integer right off the bat because n! is only defined for those numbers.

Also, this proof comes into play with what we discussed earlier.

We already discussed why (n choose n) is 1.

And, you've shown already that (n choose k) = (n choose (n-k)) right? So what happens if k=0?

I don't understand what you mean with your last sentence , I thought I already proved that if k=0 , then ##\binom{n}{k}## is an integer (1) in my post above.

I'm still trying to figure it all out , even if I fail in the end "playing" with all of this is making me understanding factorials more in depth so it can't be bad.

I'm trying to prove that ##\binom{n+1}{k}## always results in an integer from the assumption that ##\binom{n}{k}## always results as an integer.

Just trying to wrap my head around all of this and digest it to come up with a proof.I'm trying to deconstruct the entire formula using factorials but no success for the moment.I had two or three hints but all of them were wrong when I re-verified.
 
Last edited:
  • #724
reenmachine said:
I don't understand what you mean with your last sentence , I thought I already proved that if k=0 , then ##\binom{n}{k}## is an integer (1) in my post above.

I'm still trying to figure it all out , even if I fail in the end "playing" with all of this is making me understanding factorials more in depth so it can't be bad.

I'm trying to prove that ##\binom{n+1}{k}## always results in an integer from the assumption that ##\binom{n}{k}## always results as an integer.

Just trying to wrap my head around all of this and digest it to come up with a proof.

The crucial part is that we assume that ##\binom{n}{k}## is an integer for all ##k##. This is what we take as induction hypothesis. In particular, we see that ##\binom{n}{k-1}## is an integer for ##k>0##.
 
  • #725
micromass said:
The crucial part is that we assume that ##\binom{n}{k}## is an integer for all ##k##. This is what we take as induction hypothesis. In particular, we see that ##\binom{n}{k-1}## is an integer for ##k>0##.

Hmmm , so if ##\binom{n}{k}## is an integer for all ##k## , then ##\binom{n}{k-1}## is an integer for ##k>0## (even if K=0 , the final answer is 0 no? so that's still an integer (correct me if I'm wrong here)) , so basically the addition of two integers will always result in an integer , so since ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}## , then ##\binom{n+1}{k}## is an integer...
 
  • #726
reenmachine said:
Hmmm , so if ##\binom{n}{k}## is an integer for all ##k## , then ##\binom{n}{k-1}## is an integer for ##k>0## (even if K=0 , the final answer is 0 no? so that's still an integer (correct me if I'm wrong here)) , so basically the addition of two integers will always result in an integer , so since ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}## , then ##\binom{n+1}{k}## is an integer...

Right, but you need a separate argument for ##\binom{n+1}{0}##.
 
  • #727
micromass said:
Right, but you need a separate argument for ##\binom{n+1}{0}##.

Isn't it assumed from the proof of P(0)? Since ##n## is a dummy variable , what's the difference with n+1?

Let's try it anyway , assume k=0.We have ##\binom{n+1}{0} = \frac{(n+1)!}{0!((n+1)-0)!} = \frac{(n+1)!}{1 \cdot (n+1)!} = \frac{(n+1)!}{(n+1)!} = 1##.

thoughts?
thank you!
 
  • #728
reenmachine said:
Isn't it assumed from the proof of P(0)? Since ##n## is a dummy variable , what's the difference with n+1?

Technically, P(0) only says that ##\binom{0}{0}## is an integer. It doesn't say anything about ##\binom{n}{0}##. But you proved it anyway, so that's fine then.
 
  • #729
Another question , when you're facing a situation where you need to assume an argument such as Integer + Integer = Integer , do you have to prove it? This is what happened in the second part of the proof.
 
  • #730
reenmachine said:
I don't understand what you mean with your last sentence , I thought I already proved that if k=0 , then ##\binom{n}{k}## is an integer (1) in my post above.

You did, I was just showing you another way, that the things you've already proven can be applied to show that ##\binom{n}{0}=\binom{n}{n-0}=1##.

A lot of times in proof classes, when writing a proof we simplify it greatly by referencing some other theorem that we proved in the class already. It's not necessary here by any means, it's just another way.
 
Last edited:
  • #731
reenmachine said:
Another question , when you're facing a situation where you need to assume an argument such as Integer + Integer = Integer , do you have to prove it? This is what happened in the second part of the proof.

You can prove it if you want to. But in situations here, you can assume it's true.
 
  • #732
micromass said:
Technically, P(0) only says that ##\binom{0}{0}## is an integer. It doesn't say anything about ##\binom{n}{0}##. But you proved it anyway, so that's fine then.

Hmm , but I thought that the first part of the proof was that ##\binom{n}{k}## results in an integer if k=0.I thought the notation ##n## was any ##x \in \mathbb{N}##?

thank you micromass!
 
  • #733
reenmachine said:
Hmm , but I thought that the first part of the proof was that ##\binom{n}{k}## results in an integer if k=0.I thought the notation ##n## was any ##x \in \mathbb{N}##?

thank you micromass!

The induction is on ##n##, not on ##k##. So ##P(0)## says that ##\binom{0}{k}## is an integer for all ##k##.
 
  • #734
micromass said:
The induction is on ##n##, not on ##k##. So ##P(0)## says that ##\binom{0}{k}## is an integer for all ##k##.

LOL , well , this went over my head.

Because when I proved the first step , I only used 0 for k and ignored the value of n , so basically it worked for all n based on the computation of the factorials fractions (resulting in 1).
 
  • #735
What you want to prove is this, right?
For all ##n,k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​
(I'm including 0 in ##\mathbb N##). For each ##n\in\mathbb N##, let ##P(n)## be the following statement:
For all ##k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​
You want to prove all of the infinitely many statements P(0),P(1),P(2),... The way to to do that is to prove the following two statements.
\begin{align}&P(0)\\ &\forall n\in\mathbb N~~ P(n)\Rightarrow P(n+1).\end{align} P(0) is the statement
For all ##k\in\mathbb N## such that ##k\leq 0##, we have ##\binom 0 k\in\mathbb N##.​
So to prove it, the natural way to start is "Let k be an arbitrary element of ##\mathbb N## such that k≤0". This statement assigns the value 0 to k. So you can continue like this
$$\binom 0 k =\binom 0 0 =\cdots$$
(This is not the easiest example of a proof by induction, since there's a second integer variable k that makes it harder to see how to define P(n)).
 
Last edited:
  • #737
Fredrik said:
What you want to prove is this, right?
For all ##n,k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​
(I'm including 0 in ##\mathbb N##). For each ##n\in\mathbb N##, let ##P(n)## be the following statement:
For all ##k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​
You want to prove all of the infinitely many statements P(0),P(1),P(2),... The way to to do that is to prove the following two statements.
\begin{align}&P(0)\\ &\forall n\in\mathbb N~~ P(n)\Rightarrow P(n+1).\end{align} P(0) is the statement
For all ##k\in\mathbb N## such that ##k\leq 0##, we have ##\binom 0 k\in\mathbb N##.​
So to prove it, the natural way to start is "Let k be an arbitrary element of ##\mathbb N## such that k≤0". This statement assigns the value 0 to k. So you can continue like this
$$\binom 0 k =\binom 0 0 =\cdots$$
(This is not the easiest example of a proof by induction, since there's a second integer variable k that makes it harder to see how to define P(n)).

Hmm I thought I already proved it (more or less) in post 724 , 730 and 732.

Let me try it more officially.

------------------------------------------------------------------------------------------

We will attempt to prove that:
##\forall n,k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​

## \forall n\in\mathbb N##, let ##P(n)## be the following statement:
For all ##k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​

We will first attempt to prove ##P(0)##.Let ##k## be an arbitrary element of ##\mathbb N## such that ##k≤0##.This gives us ##\binom{0}{0} = \frac{0!}{0!(0-0)!} = \frac{1}{1 \cdot 1} = \frac{1}{1} = 1##.Since ##1\in\mathbb N## ,this proves ##P(0)##.

Now assume ##\binom{n}{k} \in\mathbb N## for all ##k##.This implies that ##\binom{n}{k-1} \in\mathbb N## for all ##k>0##.Since ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}## , we know that ##\binom{n+1}{k} \in\mathbb N## for all ##k>0## because it's the sum of two elements of ##\mathbb N## (which we assume as true).We're now left with ##\binom{n+1}{0}##.This equals to ##\frac{(n+1)!}{0!((n+1-0)!} = \frac{(n+1)!}{1 \cdot (n+1)!} = \frac{(n+1)!}{(n+1)!} = 1##.Since ##1 \in\mathbb N## , this proves that ##P(n) \rightarrow P(n+1)##.

These previous proofs prove that ##\forall n,k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.

-----------------------------------------------------------------------------------------

thoughts about this more official version of my proof attempt?

thank you!
 
Last edited:
  • #739
reenmachine said:
Hmm I thought I already proved it (more or less) in post 724 , 730 and 732.
Maybe you did. I didn't look closely at those posts. I just saw the "over my head" comment and assumed that the problem wasn't solved.

reenmachine said:
We will attempt to prove that:
##\forall n,k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​

## \forall n\in\mathbb N##, let ##P(n)## be the following statement:
For all ##k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​

We will first attempt to prove ##P(0)##.Let ##k## be an arbitrary element of ##\mathbb N## such that ##k≤0##.This gives us ##\binom{0}{0} = \frac{0!}{0!(0-0)!} = \frac{1}{1 \cdot 1} = \frac{1}{1} = 1##.Since ##1\in\mathbb N## ,this proves ##P(0)##.

Now assume ##\binom{n}{k} \in\mathbb N## for all ##k##.This implies that ##\binom{n}{k-1} \in\mathbb N## for all ##k>0##.Since ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}## , we know that ##\binom{n+1}{k} \in\mathbb N## for all ##k>0## because it's the sum of two elements of ##\mathbb N## (which we choose to assume as true).We're now left with ##\binom{n+1}{0}##.This equals to ##\frac{(n+1)!}{0!((n+1-0)!} = \frac{(n+1)!}{1 \cdot (n+1)!} = \frac{(n+1)!}{(n+1)!} = 1##.Since ##1 \in\mathbb N## , this proves that ##P(n) \rightarrow P(n+1)##.

These previous proofs prove that ##\forall n,k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.

-----------------------------------------------------------------------------------------

thoughts about this more official version of my proof attempt?
Looks good. Here's how I would do the ##P(n)\Rightarrow P(n+1)## step:

Let ##n\in\mathbb N## be arbitrary. Suppose that ##P(n)## holds. Let ##k## be an arbitrary element of ##\mathbb N## such that ##k\leq n##. If ##k=0##, we have
$$\binom{n+1}{k} =\frac{(n+1)!}{0!(n+1-0)!} =1\in\mathbb N.$$ If ##k>0##, we have
$$\binom{n+1}{k} =\binom n k + \binom{n}{k-1}\in\mathbb N.$$ (It follows immediately from ##P(n)## that both terms on the right are in ##\mathbb N##). So for all ##k\in\mathbb N## such that ##k\leq n##, we have ##\binom{n+1}{k}\in\mathbb N##. This means that ##P(n+1)## holds.

The only part of this that's a significant improvement over your version is the first line, which make it clear what the variables represent. I don't think that's perfectly clear in your version. For example, you say that ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}##, without making it a "for all" statement.

Note by the way that if we use my definition of n!, we have to use it to prove the identity ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}##.
 
  • #740
Fredrik said:
Maybe you did. I didn't look closely at those posts. I just saw the "over my head" comment and assumed that the problem wasn't solved.

Either way I don't think I'm strong enough yet in the "presentation" of my proofs to cut corners so it's a good idea to try my luck at some proofs once in a while :smile:

Looks good. Here's how I would do the ##P(n)\Rightarrow P(n+1)## step:

Let ##n\in\mathbb N## be arbitrary. Suppose that ##P(n)## holds. Let ##k## be an arbitrary element of ##\mathbb N## such that ##k\leq n##. If ##k=0##, we have
$$\binom{n+1}{k} =\frac{(n+1)!}{0!(n+1-0)!} =1\in\mathbb N.$$ If ##k>0##, we have
$$\binom{n+1}{k} =\binom n k + \binom{n}{k-1}\in\mathbb N.$$ (It follows immediately from ##P(n)## that both terms on the right are in ##\mathbb N##). So for all ##k\in\mathbb N## such that ##k\leq n##, we have ##\binom{n+1}{k}\in\mathbb N##. This means that ##P(n+1)## holds.

The only part of this that's a significant improvement over your version is the first line, which make it clear what the variables represent. I don't think that's perfectly clear in your version. For example, you say that ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}##, without making it a "for all" statement.

When you say that you make it clearer what the variables represent , do you mean both ##n## and ##k## being arbitrary elements of N with ##k## being equal or smaller than ##n##? Do you mean that by only using the binomial coefficients in the beginning of the second part of my proof , it remained unclear what ##k## and ##n## really are?

(take note that I do find your proof clearer myself , just wish to put my finger on why)

About not stating ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}## as a "for all" statement , do you mean that it doesn't rigorously implied that this is true for all ##n,k \in N## , so basically it looks like I was using the formula with none-arbitrary variables (or at least that I didn't eliminate the possibility that this was the case)?

Note by the way that if we use my definition of n!, we have to use it to prove the identity ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}##.

Sorry but I'm not sure in which context you're saying we should prove this identity so I'm not sure if I'm following you...

thank you!
 
Last edited:
  • #741
reenmachine said:
When you say that you make it clearer what the variables represent , do you mean both ##n## and ##k## being arbitrary elements of N with ##k## being equal or smaller than ##n##?
Yes.

reenmachine said:
Do you mean that by only using the binomial coefficients in the beginning of the second part of my proof , it remained unclear what ##k## and ##n## really are?
If your readers understand binomial coefficients and trust that you do too, then they will assume that n and k are natural numbers such that k≤n. But you should still say that explicitly. You also need to make it clear if n and k are arbitrary or if they have been assigned some specific values, like n=7, k=2. I suppose that we could use the convention that every time we don't assign values like this, and don't use the words "there exists", our statements should be interpreted as "for all" statements. But you would have to say that somewhere. I don't recommend this approach, since it doesn't save a lot of time or space, and makes the proofs a bit harder to follow.

reenmachine said:
About not stating ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}## as a "for all" statement , do you mean that it doesn't rigorously implied that this is true for all ##n,k \in N## , so basically it looks like I was using the formula with none-arbitrary variables (or at least that I didn't eliminate the possibility that this was the case)?
Yes, you didn't eliminate that possibility.
reenmachine said:
Now assume ##\binom{n}{k} \in\mathbb N## for all ##k##.
Here you left n undeclared. A simple "let ##n\in\mathbb N## be arbitrary" would have taken care of that. "For all k" is also a bit careless, since you don't mean that k can be equal to ##\pi-i##. We don't have to worry about ##\pi## and ##i## if we say that everywhere in this proof, the scope of our "for all" and "there exists" is ##\mathbb N##. But then we still have a problem with ##k## such that ##k>n##.

reenmachine said:
This implies that ##\binom{n}{k-1} \in\mathbb N## for all ##k>0##.
Same problems here.

reenmachine said:
Since ##\binom{n}{k} + \binom{n}{k-1} = \binom{n+1}{k}##
Here you say nothing about n or k.

reenmachine said:
, we know that ##\binom{n+1}{k} \in\mathbb N## for all ##k>0##
A statement that involves an undeclared k implies a statement "for all k>0"?
reenmachine said:
Sorry but I'm not sure in which context you're saying we should prove this identity so I'm not sure if I'm following you...
The book defined n! as the number of non-repeating lists with n entries, and ##\binom n k## as the number of subsets that can be made by choosing k elements from any set with n elements. I don't like these definitions. How are we supposed to use them in proofs? Consider e.g. the proof that
$$\binom{n+1}{k}=\binom n k+\binom{n}{k-1}$$ for all natural numbers n and k such that k≤n. When I read the proof discussed earlier, I pictured two boxes, the first one containing n+1 balls numbered from 0 to n, and the second one empty. Then I thought about how many ways there are to move k balls from the first box to the second. The total number must be equal to the number of ways to move k balls, none of which is numbered 0, plus the number of ways to move the one numbered 0 and k-1 more balls. Presumably, you had a similar image in your head. So are we really using the definition, or just a visual representation of our understanding of it?

I would say that it's the latter. The book's definition of ##\binom n k## means that ##\binom n k## is the cardinality of the set of all subsets of ##n=\{0,\dots,n-1\}## with cardinality ##k##. To prove that some set X has cardinality 3 for example, we would have to prove that there's a bijection from X into {0,1,2}. But we're not doing this sort of thing at all. We're just imagining some numbered balls being moved around.

So is the proof rigorous? Is it acceptable at all? These aren't easy questions. I think the answer is that proofs like this one are significantly less rigorous than the other proofs we've been doing, but are still (just barely) OK. The reason why they're OK is that the only proofs that are 100% rigorous are the ones where all the statements are written in the formal language of set theory, and it's perfectly clear in every step which axioms of our proof theory that we're using. (A proof theory is a definition of what we mean by a "proof"). The proofs we've been doing are at the level of rigor where the goal is to come up with an argument that would convince an experienced mathematician that a formal proof exists.

A mathematician with experience working with these "visual representations" of the underlying concepts will probably find the argument convincing. That's why I can't dismiss it outright. But I'm still more comfortable with definitions and proofs where we work directly with the mathematical concepts instead of some visual representations of them.

The simplest interpretation of the book's definition of n! is that n! is the cardinality of the set of injective functions from n to n, where n is defined by n={0,...,n-1}. But the book doesn't talk about cardinalities of sets of injective functions. Instead it conjures up images of things in the real world, such as numbered balls in a box, or lists written on paper. So the book's definition of n! has the same problems as its definition of ##\binom n k##.

These are the definitions I would prefer to use:

Define ##0!## by ##0!=1##. For all ##n\in\mathbb Z^+##, define ##n!## by ##n!=n(n-1)!##. For all ##n,k\in\mathbb N## such that ##k\leq n##, define
$$\binom n k =\frac{n!}{k!(n-k)!}.$$ These are simple definitions that are easy enough to use in proofs.

If we take these definitions as our starting point, a proof of ##\binom{n+1}{k}=\binom n k+\binom{n}{k-1}## that actually uses them will be much more convincing than an argument that relies on visual representations of the binomial coefficients.
 
  • #742
Fredrik said:
If your readers understand binomial coefficients and trust that you do too, then they will assume that n and k are natural numbers such that k≤n. But you should still say that explicitly. You also need to make it clear if n and k are arbitrary or if they have been assigned some specific values, like n=7, k=2. I suppose that we could use the convention that every time we don't assign values like this, and don't use the words "there exists", our statements should be interpreted as "for all" statements. But you would have to say that somewhere. I don't recommend this approach, since it doesn't save a lot of time or space, and makes the proofs a bit harder to follow.

I will try to be more explicit when I introduce variables in different contexts in the future.Thank you!

Here you left n undeclared. A simple "let ##n\in\mathbb N## be arbitrary" would have taken care of that. "For all k" is also a bit careless, since you don't mean that k can be equal to ##\pi-i##. We don't have to worry about ##\pi## and ##i## if we say that everywhere in this proof, the scope of our "for all" and "there exists" is ##\mathbb N##. But then we still have a problem with ##k## such that ##k>n##.

This is one of those tough spot for me as far as what to leave assumed or what to explicitly say.I'm talking specifically about "for all k" being careless.

I stated I wanted to prove:
##\forall n,k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​

Then defined P(N) with:

## \forall n\in\mathbb N##, let ##P(n)## be the following statement:
For all ##k\in\mathbb N## such that ##k\leq n##, we have ##\binom n k\in\mathbb N##.​

This is also without saying that the whole proof depends on factorials , are factorials assumed to be integers? Once I complete a proof it's getting easier to understand these details , but while in the process of trying to solve it , this is definitely another matter.Perhaps I should always wait a couple of hours at least before posting a proof?

A statement that involves an undeclared k implies a statement "for all k>0"?

LOL of course at this point I thought k was declared so it's not surprising that the rest of the proof doesn't make sense unless you assume what k is.

The book defined n! as the number of non-repeating lists with n entries, and ##\binom n k## as the number of subsets that can be made by choosing k elements from any set with n elements. I don't like these definitions. How are we supposed to use them in proofs? Consider e.g. the proof that
$$\binom{n+1}{k}=\binom n k+\binom{n}{k-1}$$ for all natural numbers n and k such that k≤n. When I read the proof discussed earlier, I pictured two boxes, the first one containing n+1 balls numbered from 0 to n, and the second one empty. Then I thought about how many ways there are to move k balls from the first box to the second. The total number must be equal to the number of ways to move k balls, none of which is numbered 0, plus the number of ways to move the one numbered 0 and k-1 more balls. Presumably, you had a similar image in your head. So are we really using the definition, or just a visual representation of our understanding of it?

I would say that it's the latter. The book's definition of ##\binom n k## means that ##\binom n k## is the cardinality of the set of all subsets of ##n=\{0,\dots,n-1\}## with cardinality ##k##. To prove that some set X has cardinality 3 for example, we would have to prove that there's a bijection from X into {0,1,2}. But we're not doing this sort of thing at all. We're just imagining some numbered balls being moved around.

So is the proof rigorous? Is it acceptable at all? These aren't easy questions. I think the answer is that proofs like this one are significantly less rigorous than the other proofs we've been doing, but are still (just barely) OK. The reason why they're OK is that the only proofs that are 100% rigorous are the ones where all the statements are written in the formal language of set theory, and it's perfectly clear in every step which axioms of our proof theory that we're using. (A proof theory is a definition of what we mean by a "proof"). The proofs we've been doing are at the level of rigor where the goal is to come up with an argument that would convince an experienced mathematician that a formal proof exists.

Very insightful! So which level of rigor to use when doing a proof depends of what you are trying to achieve by proving , for exemple whether you really want to prove it completely or just demonstrate to a professionnal that's it's definitely provable (even rigorously) even if you didn't bother doing it in the first place.That being said , for a mathematician it's always better to write proof as rigorously as possible.

A mathematician with experience working with these "visual representations" of the underlying concepts will probably find the argument convincing. That's why I can't dismiss it outright. But I'm still more comfortable with definitions and proofs where we work directly with the mathematical concepts instead of some visual representations of them.

See point above.

The simplest interpretation of the book's definition of n! is that n! is the cardinality of the set of injective functions from n to n, where n is defined by n={0,...,n-1}. But the book doesn't talk about cardinalities of sets of injective functions. Instead it conjures up images of things in the real world, such as numbered balls in a box, or lists written on paper. So the book's definition of n! has the same problems as its definition of ##\binom n k##.

Hmm , seems like I am a bit rusty as far as functions goes.This isn't surprising since I only covered it at the end of the 10 pages long pdf that I used in the beginning of this adventure.I then realized the function's chapter was at the end of the book of proof so I just left these concepts aside until I reach this chapter.

(I have to edit here , I expressed myself badly on some definitions)

An injective function is when each elements of the domain is paired with his own element in the co-domain.A bijection is when each elements of the domain is paired with his own element of the co-domain and that the co-domain = range.Surjective means that all elements of the co-domain are paired with some element(s) of the domain.Is that correct?

Define ##0!## by ##0!=1##. For all ##n\in\mathbb Z^+##, define ##n!## by ##n!=n(n-1)!##. For all ##n,k\in\mathbb N## such that ##k\leq n##, define
$$\binom n k =\frac{n!}{k!(n-k)!}.$$ These are simple definitions that are easy enough to use in proofs.

If we take these definitions as our starting point, a proof of ##\binom{n+1}{k}=\binom n k+\binom{n}{k-1}## that actually uses them will be much more convincing than an argument that relies on visual representations of the binomial coefficients.

This definition clearly seems better than using the cardinality of the set of all subsets of ##n=\{0,\dots,n-1\}## with cardinality ##k##.

thank you!
 
Last edited:
  • #743
This is actually quite typical in mathematics, where you take an intuitive concept such as "the number of ways to order n objects", "the surface area of a square", "a straight line" or "parallel" and make a definition which at first sight is quite unrelated. Usually, it is shown at the point where the definition is made, that it corresponds to our intuition (for example in the case of n! you could show inductively that ordering n elements means putting the first one on one of n available spots and re-ordering the rest in one of the possible (n - 1)! ways) and then always proceed to work with the (often algebraic) definition (simply because, as you have seen, a definition like 0! = 1 and n! = n(n - 1)! is more convenient in calculations).
 
  • #744
CompuChip said:
This is actually quite typical in mathematics, where you take an intuitive concept such as "the number of ways to order n objects", "the surface area of a square", "a straight line" or "parallel" and make a definition which at first sight is quite unrelated. Usually, it is shown at the point where the definition is made, that it corresponds to our intuition (for example in the case of n! you could show inductively that ordering n elements means putting the first one on one of n available spots and re-ordering the rest in one of the possible (n - 1)! ways) and then always proceed to work with the (often algebraic) definition (simply because, as you have seen, a definition like 0! = 1 and n! = n(n - 1)! is more convenient in calculations).

Thank you CompuChip!
 
  • #745
They introduce this notation in the book of proof (page 78 section 3.4) :

Use the binomial theorem to show:
##\sum \binom{n}{k=0} 3^k \binom{n}{k}=4^n##

except that the first binomial coefficient isn't between parenthesis.

I'm not sure what they mean , beside the sum symbol there's the n , k=0 on top of each other without parenthesis.

I'm in need of some help on that one.

thank you!
 
  • #746
reenmachine said:
They introduce this notation in the book of proof (page 78 section 3.4) :

Use the binomial theorem to show:
##\sum \binom{n}{k=0} 3^k \binom{n}{k}=4^n##

except that the first binomial coefficient isn't between parenthesis.

I'm not sure what they mean , beside the sum symbol there's the n , k=0 on top of each other without parenthesis.

I'm in need of some help on that one.

thank you!

They mean

\sum_{k=0}^n 3^k \binom{n}{k} = 4^n

So you sum from 0 to n.
 
  • Like
Likes 1 person
  • #747
Hey guys , I let this thread sleep a little bit as my reading of chapter 4 in the book of proof was going pretty well.I tried my luck at a couple of proofs and most of them went well but there's one that seems very simple yet I'm not sure how to prove it.

The theorem goes as follow:

If ##x \in ℝ## and ##0>x>4## , then ##\frac{4}{x(4-x)}≥1##.

We know that ##x+(4-x)=4##.This mean that the expression could be written as ##\frac{4}{m \cdot n}## with ##m,n \in ℝ## such that ##m+n=4##.Basically , I wanted to prove that for all ##y \in Z## such that ##\exists k \in Z## such that ##2k=y## , the product of any combination of ##a,b \in ℝ## such that ##a+b=y## will always be the largest if both ##a = \frac{y}{2}## and ##b = \frac{y}{2}##.

In clearer term , if you take any two elements of R that result(sum) in 4 and multiply them , you won't find a bigger one than 2 × 2= 4.Same if you take 6 as an exemple , the largest will be 3 × 3 = 9.If I proved that , it would prove the theorem since ##\frac{4}{4} = 1## and all others denominator would be smaller , resulting in a larger number than 1.

I'm lost on that one even though I have a strong feeling the answer isn't overly complicated.

thank you!
 
Last edited:
  • #748
Wait , maybe something like ##y+y=y+n+y-n## , we check ##(y)(y) = y^2## versus ##(y+n)(y-n)=y^2-n^2##? We have ##y^2>y^2-n^2## , could it prove my argument above?
 
Last edited:
  • #749
reenmachine said:
If ##x \in \mathbb{R}## and ##0>x>4## , then ##\frac{4}{x(4-x)}≥1##.
I'm sure that's not the theorem, because this is a statement about the empty set. At least I don't think you can find me any real number such that 0 > x > 4. I'll assume you meant 0 < x < 4 ;-)

In clearer term , if you take any two elements of R that result(sum) in 4 and multiply them , you won't find a bigger one than 2 × 2= 4.Same if you take 6 as an exemple , the largest will be 3 × 3 = 9.If I proved that , it would prove the theorem since ##\frac{4}{4} = 1## and all others denominator would be smaller , resulting in a larger number than 1.

That's a good approach. I don't know if you have done anything with quadratics yet, but note that y = x(4 - x) is a parabolic graph with zeroes at x = 0 and x = 4 which means that it has an extreme value right in the center at x = 2. (Try plotting it, you can use WolframAlpha if you don't know how to do this by hand yet).
How to prove that ##x(4 - x) \le 4## for all ##0 < x < 4## is a bit trickier if you have not taken analysis yet, in that case the "handwaiving" argument that x = 2 is a top of the graph is probably acceptable.
 
  • #750
CompuChip said:
I'm sure that's not the theorem, because this is a statement about the empty set. At least I don't think you can find me any real number such that 0 > x > 4. I'll assume you meant 0 < x < 4 ;-)
That's a good approach. I don't know if you have done anything with quadratics yet, but note that y = x(4 - x) is a parabolic graph with zeroes at x = 0 and x = 4 which means that it has an extreme value right in the center at x = 2. (Try plotting it, you can use WolframAlpha if you don't know how to do this by hand yet).
How to prove that ##x(4 - x) \le 4## for all ##0 < x < 4## is a bit trickier if you have not taken analysis yet, in that case the "handwaiving" argument that x = 2 is a top of the graph is probably acceptable.

Yep it was a typing mistake at the beginning.0 < x < 4 is the correct statement , I apologize for that.

I saw your post after my proof attempt in the homework forum , here's the link https://www.physicsforums.com/showthread.php?t=703655

I have very little experience with quadratic.

thank you!
 
Back
Top