The sample mean is an estimator that will consistently have an approximately normal distribution, particularly due to the Central Limit Theorem. As the sample size increases, the distribution of the sample mean approaches a normal distribution regardless of the original population's distribution, provided the samples are independent and identically distributed. This characteristic makes the sample mean a robust estimator for large sample sizes.
A "bell" shape.
No. If the underlying distribution is approximately Normal then 1.4 is not at all unusual.
To find the proportion of a normal distribution corresponding to z-scores greater than +1.04, you can use the standard normal distribution table or a calculator. The area to the left of z = 1.04 is approximately 0.8508. Therefore, the proportion of the distribution that corresponds to z-scores greater than +1.04 is 1 - 0.8508, which is approximately 0.1492, or 14.92%.
Exactly "what it says on the tin"! The distribution is nearly, but not quite, the standard normal, or Gaussiam distribution.
No, the normal distribution is strictly unimodal.
A "bell" shape.
No. If the underlying distribution is approximately Normal then 1.4 is not at all unusual.
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.
Exactly "what it says on the tin"! The distribution is nearly, but not quite, the standard normal, or Gaussiam distribution.
The standard normal distribution is a normal distribution with mean 0 and variance 1.
The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.
le standard normal distribution is a normal distribution who has mean 0 and variance 1
Between z = -1.16 and z = 1.16 is approx 0.7540 (or 75.40 %). Which means ¾ (0.75 or 75%) of the normal distribution lies between approximately -1.16 and 1.16 standard deviations from the mean.
When its probability distribution the standard normal distribution.
No, the normal distribution is strictly unimodal.
The domain of the normal distribution is infinite.
The standard normal distribution has a mean of 0 and a standard deviation of 1.