Q. 29

Question

29. The candy machine Suppose a large candy machine has 45% orange candies. Imagine taking an SRS of 25 candies from the machine and observing the sample proportion p^ of orange candies.
(a) What is the mean of the sampling distribution of p^? Why?
(b) Find the standard deviation of the sampling distribution of p^. Check to see if the 10% condition is met.
(c) Is the sampling distribution of p^approximately Normal? Check to see if the Normal condition is met.
(d) If the sample size were 50 rather than 25, how would this change the sampling distribution of p^?

Step-by-Step Solution

Verified
Answer

(a) The mean of the sampling distribution p^ is 0.45.

(b) The standard deviation is 0.099487.

(c) The sampling distribution of p^ is approximately Normal.

(d) The standard deviation of the sampling distribution p^ changes to 0.070356 with the sample size is n=50.

1Part (a) Step 1: Given information

To determine the mean of the sampling distribution of p^.

2Part (a) Step 2: Explanation

Let the sample distribution to be pand the SRS sample size to be n.
p=45%
=0.45
Then, n=25

The mean of a sample proportion's sampling distribution p^ and the population proportion p are equivalent.

μp^=p.

Let, substitute the value 0.45 for p as:

μp^=0.45

The mean is calculated using the sampling proportion as an unbiased estimator of the population percentage.

As a result, the mean of the sampling distribution p^ is 0.45.

3Part (b) Step 1: Given information

To  find the standard deviation of the sampling distribution of p^. Then to check to see if the 10% condition is met.

4Part (b) Step 2: Explanation

Let, the sample distribution to be p and the sample size for SRS to be n.
p=45%

=0.45

Then, n=25

The standard deviation of the sampling distribution of p^ is σp^=p(1-p)n.

Let, substitute the value 0.45 for p.

Also substitute the value, 25 for n .
σp^=0.45(1-0.45)25
=0.45×0.5525
=0.0099

0.0994987

The candy machine is enormous, it contains more than 250 candies, so satisfying the 10% criterion.

As a result, the standard deviation is 0.099487.

5Part (c) Step 1: Given information

To find the sampling distribution of p^ is approximately normal or not.

6Part (c) Step 2: Explanation

The sampling distribution is roughly Normal when the product of sample size and sampling proportion, that is, np and n(1-p), are both less than or equal to 10.
Let, the sample distribution to be p and sample size for SRS to be n.
p=45%
=0.45
Then, n=25
If the product of the sample size and the sampling proportion, np and n(1-p), are both less than 10, the sampling distribution is nearly Normal.

Let, substitute the value 0.45 for pand the value 25 for n in the term np.
25×(0.45)

=11.25

7Part (c) Step 3: Explanation

Then, substitute the value 0.45 for p and the value 25for n in the term  n(1-p).
25(1-0.45)=25×0.55
=13.75
Because both np and n(1-p) are at least 10 the Normal distribution requirement is met.
As a result, the sampling distribution of p^ is approximately Normal.

8Part (d) Step 1: Given information

The sample size were 50 rather than 25, and  change the sampling distribution of p^.

9Part (d) Step 2: Explanation

Let, the sample distribution to be p and the sample size for SRS to be n.
p=45%

=0.45

n=50

The standard deviation of the sampling distribution of p^ is calculated by:σp^=p(1-p)n.

Then, substitute the value 0.45 for p and the value 50 for n as:

σp^=0.45(1-0.45)50

=0.45×0.5550

=0.00495

0.0703562

As a result, the standard deviation is 0.0703562.