Basic statistics/probability question

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In summary, the probability of getting killed in a specific round (like the next one) stays constant at 1/6, but the probability of getting killed in any round within the first n rounds increases with increasing n. This is because with every additional round, another 1/6 chance of getting killed gets introduced into the picture.
  • #1
vanizorc
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Moderator note: moved to homework section

I'm not quite sure how to frame this question/thought of mine, as I'm not a math/physics student, but here goes: say you're in a game of Russian Roulette where the probability in each round of getting killed is 1/6. I need to show that, with more rounds that occur, the probability of getting killed will correspondingly increase (despite the fact that the 1/6 chance of getting killed in each round will remain constant). So for example, the probability of getting killed after 3 rounds is less than the probability of getting killed after 9 rounds.

Does anyone know how to show the formula for such a thought experiment?
 
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  • #3
I think your question is ambiguous. If you mean "The chance of being killed in three rounds" (i.e on the first, second, or third rounds) is less than the chance of being killed in nine rounds" then you can calculate- the chance of being killed in the first round is 1/6. If you are not killed on the first round (probability 5/6), your chance of being killed on the second round is also 1/6. If you are not killed on the first or second round (probability (5/6)^2= 25/36), your chance of being killed on the third round is also 1/6. Your chance of being killed on one of the first three rounds is 1/6+ (5/6)(1/6)+ (5/6)(5/6)(1/6), the "Geometric distribution" Stephen Tashi references. You chance of being killed on one of the first nine rounds is that plus the probability of being killed on the fourth, fifth, sixth, seventh, eighth, or ninth rounds so, of course, it is larger.

But if you mean "given that you were not killed on the first two rounds, the chance of being killed on the third round" and "given that you were not killed on the first eight rounds, the chance of being killed on the ninth round", one is NOT larger than the other, they are both exactly 1/6.
 
  • #5
HallsofIvy said:
I think your question is ambiguous. If you mean "The chance of being killed in three rounds" (i.e on the first, second, or third rounds) is less than the chance of being killed in nine rounds" then you can calculate- the chance of being killed in the first round is 1/6. If you are not killed on the first round (probability 5/6), your chance of being killed on the second round is also 1/6. If you are not killed on the first or second round (probability (5/6)^2= 25/36), your chance of being killed on the third round is also 1/6. Your chance of being killed on one of the first three rounds is 1/6+ (5/6)(1/6)+ (5/6)(5/6)(1/6), the "Geometric distribution" Stephen Tashi references. You chance of being killed on one of the first nine rounds is that plus the probability of being killed on the fourth, fifth, sixth, seventh, eighth, or ninth rounds so, of course, it is larger.

But if you mean "given that you were not killed on the first two rounds, the chance of being killed on the third round" and "given that you were not killed on the first eight rounds, the chance of being killed on the ninth round", one is NOT larger than the other, they are both exactly 1/6.

Your former interpretation of my question is what I had meant. Basically, that even though the probability of getting killed in each round stays stagnant at 1/6, you nevertheless have an increasing chance of getting killed with a greater number of rounds you're put through. This question of mine came about because, during a discussion with a friend, my friend claimed that the probability of being killed in Russian Roulette stays the same no matter how many rounds you go through, and I rebutted that this is incorrect because with every additional round, another 1/6 chance of getting killed gets introduced into the picture.
 
  • #6
Your friend probably refers to the probability of getting killed in a specific round (like "the next one"), if you survive all previous rounds: this is indeed constant (it is 1/6).
The probability to get killed in some round within the first n increases with increasing n, of course.
 
  • #7
vanizorc said:
Your former interpretation of my question is what I had meant. Basically, that even though the probability of getting killed in each round stays stagnant at 1/6, you nevertheless have an increasing chance of getting killed with a greater number of rounds you're put through. This question of mine came about because, during a discussion with a friend, my friend claimed that the probability of being killed in Russian Roulette stays the same no matter how many rounds you go through, and I rebutted that this is incorrect because with every additional round, another 1/6 chance of getting killed gets introduced into the picture.

Both you and your friend are right, because you are (likely) talking about different things, but using the same words.
 

1. What is the difference between statistics and probability?

Statistics is a branch of mathematics that deals with collecting, analyzing, and interpreting data. It involves methods for organizing, summarizing, and presenting data, as well as making inferences and predictions based on data. Probability, on the other hand, is a branch of mathematics that deals with the likelihood of events occurring. It involves the study of random phenomena and the use of mathematical tools to model and analyze uncertainty.

2. How are mean, median, and mode different from each other?

Mean, median, and mode are all measures of central tendency, but they differ in how they represent the "average" value of a data set. Mean is the sum of all values in a data set divided by the number of values. Median is the middle value in a data set when the values are arranged in ascending or descending order. Mode is the most frequently occurring value in a data set. While mean and median can be affected by extreme values, mode is not affected by outliers.

3. What is the difference between descriptive and inferential statistics?

Descriptive statistics involves summarizing and presenting data in a meaningful way, such as through tables, graphs, and numerical measures. It is used to describe and understand a data set. Inferential statistics, on the other hand, involves using sample data to make generalizations or predictions about a larger population. It helps in drawing conclusions and making decisions based on limited data.

4. How do you calculate probability?

To calculate probability, you need to divide the number of favorable outcomes by the total number of possible outcomes. The formula is P(A) = Number of favorable outcomes / Total number of possible outcomes. For example, if you want to find the probability of getting a 3 when rolling a fair six-sided die, the possible outcomes are 1, 2, 3, 4, 5, 6 and the favorable outcome is 1 (only one side has a 3). Therefore, the probability is 1/6 or 0.167.

5. What is the difference between independent and dependent events in probability?

Independent events are events where the occurrence of one event does not affect the occurrence of another event. For example, flipping a coin and rolling a die are independent events. Dependent events, on the other hand, are events where the occurrence of one event affects the occurrence of another event. For example, picking two cards from a deck without replacement is a dependent event because the probability of picking the second card depends on the outcome of the first pick.

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