silemus.
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  1. 1Probability of even on a die
  2. 2P(sum=7)P(\text{sum} = 7) with two dice
  3. 3Sum of two dice ≥10\ge 10
  4. 4Exactly 2 heads in 3 tosses
  5. 5Binomial probability P(X=5)P(X = 5)
  6. 6Binomial P(X=0)P(X = 0)
  7. 7Binomial P(X≥1)P(X \ge 1)
  8. 8Mean and variance, Binomial
  9. 9Poisson P(X=0)P(X = 0)
  10. 10Poisson probability P(X=2)P(X = 2)
  11. 11Poisson P(X≤1)P(X \le 1)
  12. 12Expected value, geometric distribution
  13. 13Choosing 3 from 10
  14. 15Choosing 2 women, 1 man
  15. 17At least one six in 4 rolls
  16. 19Conditional probability P(A∣B)P(A \mid B)
  17. 20Union of independent events
  18. 24Expected value of a die
  19. 25Variance of a die roll
  20. 26Expected value of XX
  21. 27Variance of a discrete XX
  22. 28Linear transform of E[X]E[X] and Var(X)\mathrm{Var}(X)
  23. 29Variance of independent sum
  24. 30Uniform probability P(X>7)P(X > 7)
  25. 31Uniform mean and variance
  26. 32Exponential tail probability
  27. 33Exponential wait probability
  28. 36Probability from a density
  29. 37Normal probability, zz-score
  30. 38Normal probability, 40<X<6040 < X < 60
  31. 39zz-score of a normal value
  32. 40Standard error of the mean
  33. 43Sample mean and variance
  34. 44Median of a data set
  35. 47Independence of two events
  36. 49Expected heads in 50 tosses
  37. 52Bayes with a probability tree

25Variance of a die roll

Find the variance of one roll of a fair die. Give the answer to 4 decimal places.

Variance is the average squared distance from the mean: E[X²] − (E[X])². The mean is 3.5, E[X²] = 91/6 ≈ 15.1667, so Var(X) = 91/6 − 12.25 = 35/12 ≈ 2.9167.

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