Optimizing Random Variates in Simulations for Basic Statistics Problems

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In summary, the conversation discussed a theoretical question about a basic statistics problem involving random variates. One person used 20 simulations of the World Series final with a U(0,1) distribution, while the other person used an ordered set of 7 variates for each simulation. Both methods resulted in a winner being determined, but one person's method may have taken longer due to unnecessary calculations.
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CaptainP
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Pretty theoretical question here. I was talking with one of my friends the other day about a basic statistics problem that utilizes random variates. The problem asked us to perform 20 simulations of the world series final using a U(0,1) distribution. One team was given a probability of winning a given game of .55, the other team .45, and the series is won best 4 out of 7. My friend would generate one variate at a time representing each game as it was played, so some of his simulations used just 4 variates while others used 5, 6, or 7. I generated an ordered set of 7 variates for every single simulation, and worked my way through them until a winner was determined, so some of the simulations did not utilize all of the variates generated for them. Is my method improper? Is there something wrong with "skipping" or "wasting" random variates like I did?
 
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I don't see a problem with unnecessary calculations. It might need more CPU time, but for those small numbers this is completely negligible.
 

1. What are wasted random variates?

Wasted random variates refer to generated random numbers that are not used for the intended purpose of a simulation or experiment. In other words, they do not contribute to the final results and are considered "wasted" or unnecessary.

2. How do wasted random variates occur?

Wasted random variates can occur due to errors in programming or simulation design, or when the random number generator produces more numbers than needed for the experiment.

3. What is the impact of wasted random variates on the results of a study?

The impact of wasted random variates depends on the specific study and the amount of wasted numbers. In some cases, it may not have a significant effect on the results, but in others, it can lead to biased or inaccurate conclusions.

4. Can wasted random variates be avoided?

Yes, wasted random variates can be avoided by carefully designing simulations and experiments and ensuring that the random number generator is producing the exact number of numbers needed for the study. Regularly checking for errors in programming can also help prevent wasted random variates.

5. How can the effects of wasted random variates be mitigated?

If wasted random variates do occur, they can be mitigated by increasing the sample size to make up for the lost data points. However, this may not always be possible or practical, so it is important to try to avoid wasted random variates in the first place.

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