To apply the central limit theorem to the sampling distribution of the sample mean, the sample is usually considered to be large if the sample size, n, is greater than:

Consider the following CDF for the continuous uniform random variable X:

, for 

What is the median of X?

A passenger metal detector at Lisbon's Airport gives an alarm 2.1 times a minute, on average.

What is the probability that more than 30 seconds will pass before the next alarm?

The tensile strength X of paper, in pounds per square inch, has μ = 30 and σ = 3. A random sample of size n = 100 is taken from the distribution of tensile strengths. Compute the probability that the sample mean is greater than 29.7 pounds per square inch.

Which of the following could not be probability density functions for a continuous random variable?

(A)  for 

(B)  for 

(C)  for 

Select all that apply.

The tensile strength X of paper, in pounds per square inch, has μ = 30 and σ = 3. A random sample of size n = 100 is taken from the distribution of tensile strengths. Compute the probability that the sample mean is greater than 29.5 pounds per square inch.

According to the central limit theorem, the sampling distribution of the mean can be approximated by the normal distribution: