http://www.ck12.org Chapter 7. Sampling Distributions and Estimations
The shaded area shows the probability that the sample mean is less than 1.5.
Thez−score for the value 1.5 isz=x ̄−σxμ ̄x ̄≈^1. 05 −. 270.^8 ≈ 2. 6
As shown above, the area under the standard normal curve to the left of 1.5 (az−score of 2.6) is approximately
0 .9937. This value can also be determined by using the graphing calculator
The probability that the sample mean will be below 1.5 is 0.9937. In a random sample of 20 families, it is almost
definite that the average number of pets per family will be less than 1.5.
These three properties associated with the Central Limit Theorem are displayed in the diagram below:
The vertical axis now readsprobability densityrather thanfrequency. Frequency can only be used when you are
dealing with a finite number of sample means, as it is the number of selections divided by the total number of sample
means. Sampling distributions, on the other hand, are theoretical depictions of an infinite number of sample means,
and probability density is the relative density of the selections from within this set.
Example:
A random sample of size 40 is selected from a known population with a mean of 23.5 and a standard deviation of
4 .3. Samples of the same size are repeatedly collected allowing a sampling distribution of the sample mean to be
drawn.
a) What is the expected shape of the resulting distribution?
b) Where is the sampling distribution of the sample mean centered?
c) What is the standard deviation of the sample mean?
Solution:
The question indicates that an infinite number of samples of size 40 are being collected from a known population,
an infinite number of sample means are being calculated and then the sampling distribution of the sample mean is
being studied. Therefore, an understanding of the Central Limit Theorem is necessary to answer the question.
a) The sampling distribution of the sample mean will be bell-shaped.
b) The sampling distribution of the sample mean will be centered about the population mean of 23. 5