As a general rule, the normal distribution is used to approximate the sampling distribution of the sample mean only if
the sample size n is sufficiently large
举一反三
- Which of the following is true about the sampling distribution of the sample mean? A: The mean of the sampling distribution is always μ. B: The standard deviation of the sampling distribution is always σ. C: The shape of the sampling distribution is always approximately normal. D: D) All the alternatives are correct
- If n samples are extracted from any population with mean value [img=11x18]1803dc1a4012523.png[/img] and variance [img=18x22]1803dc1a48a9511.png[/img], then A: When n is sufficiently large, the distribution of sample mean is approximately normal distribution. B: When n<10, the distribution of sample mean is approximately normal distribution. C: The distribution of sample mean is nothing to do with n. D: No matter how big n is, the distribution of the sample mean is not going to be close to a normal distribution.
- 中国大学MOOC: A population distribution is normal with a mean of 18 and standard deviation of 4. A sample of 16 observations is selected and a sample mean computed. What is the probability that the sample mean is more than 18?
- A standard normal distribution is a normal distribution with:
- For any normal distribution, any value less than the mean would have a _______.
内容
- 0
In order to use the normal distribution for interval estimation of m when s is known, the population A: must be very large B: must have a normal distribution C: can have any distribution D: must have a mean of at least 1
- 1
The normal approximation to the binomial distribution works best when the number of trials is large, and when the binomial distribution is symmetrical (like the normal).
- 2
Gaussian distribution A: equal probability B: normal distribution C: area of a circle D: hash table
- 3
The probability mass between two standard deviations around the mean for a normal distribution is ________.（ ） A: 66% B: 90% C: 75% D: 95%
- 4
Which of the following about the normal distribution is NOT true?