Probability problem from Pokemon cards

In summary: The damage done when rolling n consecutive tails and then a head is, of course, 20n. The probability of rolling n consecutive tails and then a head is, as above, (1/2)n+1. So the average damage (the expected value) is the sum \sum_{n=1}^\infty n (1/2)^{n+ 1}. We can factor 1/4= (1/2)^2 out of that to get (1/4)\sum_{n= 1}^\infty n(1/2)^{n-1}
  • #1
Bipolarity
776
2
A long time ago when I played with Pokemon cards, I remember a Geodude card saying "Flip a coin until you get tails. This attack does 20 damage times the number of heads."

What would be the probability that the attack does more than 60 damage?

What would be the average damage of the attack if the attack were repeated indefinitely and its damage measured for each trial.

The problem popped into my mind as I am reading on probability, but any thoughts on how to solve this problem? I think of geometric probability distributions, but can't quite establish a solution.

BiP
 
Physics news on Phys.org
  • #2
Hi Bipolarity! :wink:

It's probably one of those ∑ xn = 1/(1-x) manoeuvres.

Show us how far you've got. :smile:
 
  • #3
I understand that it is a geometric sum of some sort, but I'm not so clear about the connection between geometric progressions and probability.

Would it be correct in saying that the probability that the attack does more than 60 damage is sum of the probabilities that the attack does damages corresponding to 80,100,120,140... ad infinitum?

That I think I get, but beyond that, how would you calculate the individual probabilities?

And I have no clue how to calculate the average damage. I assume you would take each value, multiply it by its probability to give it a weight, and sum up all such weights, but I am used to doing this in continuous variables using calculus. I don't know how you find infinite sums for these types of problems.

BiP
 
  • #4
Bipolarity said:
Would it be correct in saying that the probability that the attack does more than 60 damage is sum of the probabilities that the attack does damages corresponding to 80,100,120,140... ad infinitum?

yes, but easier is to say that it's 1 minus the probability of 20 40 or 60 :wink:
That I think I get, but beyond that, how would you calculate the individual probabilities?

P(20k) = P(k-1 tails then 1 heads)
And I have no clue how to calculate the average damage. I assume you would take each value, multiply it by its probability to give it a weight, and sum up all such weights, but I am used to doing this in continuous variables using calculus. I don't know how you find infinite sums for these types of problems.

Yes, ∑ 20kP(20k) …

try it and see :smile:
 
  • #5
It will do 0 damage if you flip tails on the first flip- the probability of that is 1/2.
It will do 20 damage if you flip tails and then heads- the probability of that is (1/2)(1/2)= 1/4.
It will do 40 damage if you flip tails twice and then heads- the probability of that (1/2)2(1/2)= 1/8.
It will do 60 damage if you flip tails three times and then heads- the probability of that is (1/2)3(1/2)= 1/16.

Now, what is the probability it will do damage of "60 or less"? What is the probability it will do damage of "more than 60"? Do you see what that has to do with a geometric series?

The damage done when rolling n consecutive tails and then a head is, of course, 20n. The probability of rolling n consecutive tails and then a head is, as above, (1/2)n+1. So the average damage (the expected value) is the sum [itex]\sum_{n=1}^\infty n (1/2)^{n+ 1}[/itex]. We can factor [itex]1/4= (1/2)^2[/itex] out of that to get [itex](1/4)\sum_{n= 1}^\infty n(1/2)^{n-1}[/itex]

The reason I do that is that [itex]n x^{n-1}[/itex] is the derivative of [itex]x^n[/itex]. Further, power series are "term by term" differentiable so that our sum is 1/4 times the derivative of the [itex]\sum x^n= \frac{1}{1-x}[/itex], evaluated at x= 1/2.
 
Last edited by a moderator:
  • #6
Thank you all. I understand it now.

BiP
 

Related to Probability problem from Pokemon cards

What is a probability problem from Pokemon cards?

A probability problem from Pokemon cards is a mathematical question that involves calculating the likelihood of certain events occurring when drawing cards from a deck of Pokemon trading cards.

How do you calculate the probability of pulling a specific card from a deck?

The probability of pulling a specific card from a deck can be calculated by dividing the number of desired cards by the total number of cards in the deck. For example, if there are 20 Pikachu cards out of a total of 100 cards in the deck, the probability of pulling a Pikachu card is 20/100 or 20%.

What is the difference between theoretical and experimental probability?

Theoretical probability is the probability of an event occurring based on mathematical calculations. Experimental probability is the probability of an event occurring based on the results of an experiment or real-life trial.

How does the rarity of a Pokemon card affect its probability of being drawn?

The rarity of a Pokemon card affects its probability of being drawn by changing the number of cards available in the deck. Rare cards are usually more difficult to obtain, meaning there are fewer of them in the deck and therefore a lower probability of being drawn.

How can probability be used to determine the value of a Pokemon card?

Probability can be used to determine the value of a Pokemon card by considering the rarity and desirability of the card. Cards with a lower probability of being drawn are usually more valuable, as they are harder to obtain. Additionally, cards with a higher probability of being drawn may be less valuable due to their abundance in the deck.

Similar threads

  • Set Theory, Logic, Probability, Statistics
2
Replies
57
Views
2K
  • Set Theory, Logic, Probability, Statistics
2
Replies
45
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
Replies
15
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
16
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
7
Views
2K
Back
Top