Skip to main content
Cross Validated

Return to Answer

added 1 character in body
Source Link
Dave
Dave
  • 67k
  • 7
  • 105
  • 305

Data drawn from a normanormal distribution assures that the z-score has a normal distribution. The central limit theorem only says that the z-score converges to normality, and it doesn’t even say how fast, so our 30 samples might not result in a very normal-like z-score (though the convergence is often quite fast...while it’s just a joke, there’s a reason that I say that statisticians think $30=\infty$).

Data drawn from a norma distribution assures that the z-score has a normal distribution. The central limit theorem only says that the z-score converges to normality, and it doesn’t even say how fast, so our 30 samples might not result in a very normal-like z-score (though the convergence is often quite fast...while it’s just a joke, there’s a reason that I say that statisticians think $30=\infty$).

Data drawn from a normal distribution assures that the z-score has a normal distribution. The central limit theorem only says that the z-score converges to normality, and it doesn’t even say how fast, so our 30 samples might not result in a very normal-like z-score (though the convergence is often quite fast...while it’s just a joke, there’s a reason that I say that statisticians think $30=\infty$).

Source Link
Dave
Dave
  • 67k
  • 7
  • 105
  • 305

Data drawn from a norma distribution assures that the z-score has a normal distribution. The central limit theorem only says that the z-score converges to normality, and it doesn’t even say how fast, so our 30 samples might not result in a very normal-like z-score (though the convergence is often quite fast...while it’s just a joke, there’s a reason that I say that statisticians think $30=\infty$).