Probability of skill at board games

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SUMMARY

This discussion focuses on determining the probability that a higher score in board games reflects a player's skill rather than random chance. It emphasizes the use of statistical methods such as the independent z-test for comparing average scores when the sample size is large (N ≥ 30) and the independent t-test for smaller samples (N < 30). Additionally, it highlights the necessity of employing nonparametric methods, like rank sum tests, when the score distributions are not normal or have significantly different standard deviations.

PREREQUISITES
  • Understanding of normal distribution in statistics
  • Knowledge of independent z-test and t-test
  • Familiarity with nonparametric methods in statistics
  • Basic concepts of standard deviation and average scores
NEXT STEPS
  • Research the application of the independent z-test for comparing means
  • Learn about the independent t-test and its assumptions
  • Explore nonparametric statistical methods, specifically rank sum tests
  • Study the implications of sample size on statistical testing
USEFUL FOR

Statisticians, game designers, and anyone interested in analyzing skill versus luck in competitive board games.

Gerenuk
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In many board games points are counted.
Does some know the result to the following question?
Assume that in each round points are given according to some normal distribution and points over the rounds are added up. Now say after N rounds the score of two players is X and Y. What is the chance that the higher score really belongs to a more skilled player (higher average in one round) and is not just a random result? Can I say something about the difference in average scores per round? For example how many standard deviations are between them?

(or which other assumptions do I need to include to pose this question?)

I'm not familiar with all concepts of statistics, but maybe someone can tell me where to plug in X, Y and N to get my result? :smile:
 
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Player x and y can have a specific amount of points for each of each round, after N rounds x has set of points and y has his own set of points too. You can use independent z test on average points per round between x set and y set. If the N is small say < 30, you can use independent t test. If distribution of x and y are not normal and have very different standard deviations. You should use nonparametric methods, like rank sum based tests.
 

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