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
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
举一反三
- For any normal distribution, any value less than the mean would have a _______.
- 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.
- 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).
- In determining an interval estimate of a population mean when σ is unknown, we use a t distribution with n - 1 degrees of freedom.
- A standard normal distribution is a normal distribution with: