Justifying Linear Interpolation in Coin Toss Example

Click For Summary

Discussion Overview

The discussion revolves around the justification of linear interpolation in the context of a coin toss example used in a probability scenario. Participants explore the recursive relationship of a function representing the probability of reaching a certain fortune in a gambling game, examining the implications of this relationship on the linearity of the function.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant questions the justification for assuming that the recursive function ψ(z) is linear, seeking clarity on the professor's mention of linear interpolation.
  • Another participant suggests that the linear form of ψ can be viewed as a hypothesis, noting that only one equation satisfies the recurrence relation given the initial conditions.
  • Some participants discuss the characteristic equation of the recurrence relation, indicating that it has only one solution, r = 1, which implies linearity according to the theory of linear recurrence relations.
  • One participant expresses confusion about the characteristic equation being a polynomial and seeks clarification on its implications.
  • Another participant explains that the recurrence relation implies that the differences in ψ(z) are constant, which supports the conclusion that ψ(z) is linear.
  • Several participants agree that the relationship between ψ(z), ψ(z+1), and ψ(z-1) indicates that ψ(z) increases by the same amount for each increment in z, reinforcing the linearity argument.

Areas of Agreement / Disagreement

Participants generally agree on the linearity of the function ψ(z) based on the recurrence relation, but there are varying degrees of understanding regarding the underlying theory and implications of the characteristic equation. Some confusion remains about the details of the mathematical justification.

Contextual Notes

Participants reference the general theory of linear recurrence relations and the characteristic polynomial, but there are unresolved questions about the specifics of these concepts and their application to the problem at hand.

Mogarrr
Messages
120
Reaction score
6
Today in class, there was an example where I didn't understand certain justifications. The example goes something like this:

A casino runs a game of chance where you toss a coin and they pay $1 if you get heads , and you pay $1 if you get tails. The coin is a fair coin.

A gambler starts with fortune z. The goals is to increase the fortune to g≥z. Said gambler plays until they reach g or their fortune is $0.

Let A be the event of reaching the goal g starting from fortune z.
Let Pr(A) = ψ(z).

It's clear that ψ(0)=0 and ψ(g)=1, by the rules the gambler uses. We want a formula ψ(z) for 0<z<g. We use the law of total probability, conditioning on the first toss.
Let B_1=first toss is heads
Let B_2=first toss is tails, as this forms a partition of the sample space.

Pr(A)=Pr(B_1)\cdot Pr(A|B_1) + Pr(B_2)\cdot Pr(A|B_2), so
ψ(z) = (1/2)ψ(z+1) + (1/2)ψ(z-1) = (1/2)(ψ(z+1)+ψ(z-1))

and this is where I have a big question mark over my head

ψ(z) is a linear function of z

\exists a,b: ψ(z)=az+b
\psi (0)=0 \Rightarrow b=0
\psi (g) =1 \Rightarrow a = \frac 1{g}
\Rightarrow \psi (z)= \frac {z}{g}, \forall z: 0 \leq z \leq g

...So how is it justified that the recursive function is a linear function. The professor talked about a linear interpolation happening, but I just don't see how you can make that jump. I can follow all other lines of reasoning, so I just want to talk about this.

Anybody here know how that step is justified?
 
Physics news on Phys.org
One way of thinking about that ##\psi## has the form of a linear equation is as a hypothesis. Only one equation will satisfy the recurrence relation given the two initial conditions. The general linear function has a solution in its coefficients, and so the hypothesis was correct, and the calculation yields the exact equation for ##\psi##.

But one can also deduce this without hypothesis of the form of ##\psi##. The characteristic equation for the recurrence relation has only one solution r = 1, and therefore we know the equation is linear, by the general theory of linear recurrence relations in one variable. Calculating the coefficients still remain however.
 
disregardthat said:
But one can also deduce this without hypothesis of the form of ##\psi##. The characteristic equation for the recurrence relation has only one solution r = 1, and therefore we know the equation is linear, by the general theory of linear recurrence relations in one variable. Calculating the coefficients still remain however.

I don't really follow. I think the characteristic equation is a polynomial, right? What do you mean when you say it has only one solution, r=1? And the general theory of linear recurrence relations in one variable?
 
Mogarrr said:
I don't really follow. I think the characteristic equation is a polynomial, right? What do you mean when you say it has only one solution, r=1? And the general theory of linear recurrence relations in one variable?

Read up some on recurrence relations. See for example here: http://en.wikipedia.org/wiki/Recurrence_relation#Solving
they do the general case for a recurrence relation in one variable, and what form it has when the characteristic roots are equal (in this case, equal to 1).

But this is of course much better explained in any book that covers this material.

To answer your questions, yes the characteristic equation is a polynomial equation (the characteristic polynomial = 0). It is a second-order polynomial equation, having two roots up to multiplicity.
 
  • Like
Likes   Reactions: 1 person
Mogarrr said:
ψ(z) = (1/2)ψ(z+1) + (1/2)ψ(z-1) = (1/2)(ψ(z+1)+ψ(z-1))

The way I see it is if the above occurrence relation holds then

ψ(z+1) - ψ(z) = ψ(z) - ψ(z-1)

for any 0<z<g. That means ψ(z) must increase by the same amount with every increment in z (same difference going from z-1 to z as from z to z+1) or in other words, ψ(z) is linear.
 
  • Like
Likes   Reactions: 1 person
rikblok said:
The way I see it is if the above occurrence relation holds then

ψ(z+1) - ψ(z) = ψ(z) - ψ(z-1)

for any 0<z<g. That means ψ(z) must increase by the same amount with every increment in z (same difference going from z-1 to z as from z to z+1) or in other words, ψ(z) is linear.

I see, so

\psi (z) = \frac 12 (\psi (z+1) + \psi (z-1)) \Rightarrow 2\cdot \psi (z) = \psi (z+1) + \psi (z-1)
\Rightarrow \psi (z) - \psi (z-1) = \psi (z+1) - \psi(z)

And as you say, ψ(z) increases by the same amount with every increment.

Very nice and easy to understand point.
 

Similar threads

  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 20 ·
Replies
20
Views
6K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 28 ·
Replies
28
Views
6K
  • · Replies 3 ·
Replies
3
Views
1K
  • · Replies 10 ·
Replies
10
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K