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Is it appropriate to use the normal distribution to approximate the sampling distribution of \(\hat{p}\) in the following circumstances? a. \(n=50, p=.05\) b. \(n=75, p=.1\) c. \(n=250, p=.99\)

Short Answer

Expert verified
a) n = 50, p = 0.05 b) n = 75, p = 0.1 c) n = 250, p = 0.99 **Answer** a) No, it is not appropriate, as the condition \(np \geq 10\) is not met. b) No, it is not appropriate, as the condition \(np \geq 10\) is not met. c) No, it is not appropriate, as the condition \(n(1-p) \geq 10\) is not met.

Step by step solution

01

Part a: n = 50, p = 0.05

First, let's check if the sample size is large enough and if the two conditions are met: \(n = 50\) \(p = 0.05\) Condition 1: \(np = 50 * 0.05 = 2.5\) Condition 2: \(n(1-p) = 50 * (1 - 0.05) = 47.5\) The sampling distribution does not meet the condition \(np \geq 10\). So, it is not appropriate to use the normal distribution to approximate the sampling distribution of \(\hat{p}\) for this circumstance.
02

Part b: n = 75, p = 0.1

Let's check if the sample size is large enough and if the two conditions are met: \(n = 75\) \(p = 0.1\) Condition 1: \(np = 75 * 0.1 = 7.5\) Condition 2: \(n(1-p) = 75 * (1 - 0.1) = 67.5\) The sampling distribution does not meet the condition \(np \geq 10\). So, it is not appropriate to use the normal distribution to approximate the sampling distribution of \(\hat{p}\) for this circumstance.
03

Part c: n = 250, p = 0.99

Let's check if the sample size is large enough and if the two conditions are met: \(n = 250\) \(p = 0.99\) Condition 1: \(np = 250 * 0.99 = 247.5\) Condition 2: \(n(1-p) = 250 * (1 - 0.99) = 2.5\) The sampling distribution does not meet the condition \(n(1-p) \geq 10\). So, it is not appropriate to use the normal distribution to approximate the sampling distribution of \(\hat{p}\) for this circumstance. In conclusion, for all three circumstances provided, it is not appropriate to use the normal distribution to approximate the sampling distribution of \(\hat{p}\).

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