32 if you sample is a random sample.
Other methods look at the shape of the data and how skewed it is.
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Don't know what "this" is, but all symmetric distributions are not normal. There are many distributions, discrete and continuous that are not normal. The uniform or binomial distributions are examples of discrete symmetric distibutions that are not normal. The uniform and the beta distribution with equal parameters are examples of a continuous distribution that is not normal. The uniform distribution can be discrete or continuous.
0.674 sd.
Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.Because many naturally occurring variables were approximately distributed according to a Normal bell shaped curve.
It depends on the shape of the distribution. For standard normal distribution, a two tailed range would be from -1.15 sd to + 1.15 sd.
Only one. A normal, or Gaussian distribution is completely defined by its mean and variance. The standard normal has mean = 0 and variance = 1. There is no other parameter, so no other source of variability.