In Exercises, use the same population of {4, 5, 9} that was used in Examples 1 and 2. As in Examples 1 and 2, assume that samples of size n=2 are randomly selected with replacement. Sampling Distribution of the Sample Proportion a. For the population, find the proportion of odd numbers. b. Table 6-3 describes the sampling distribution of the sample mean. Construct a similar table representing the sampling distribution of the sample proportion of odd numbers. Then combine values of the sample proportion that are the same, as in Table 6-4. ( Hint: See Example 1 for Tables 6-3 and 6-4 that describe the sampling distribution of the sample mean.) c. Find the mean of the sampling distribution of the sample proportion of odd numbers. d. Based on the preceding results, is the sample proportion an unbiased estimator of the population proportion? Why or why not? Example 1 Sampling Distribution of the Sample Mean

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...