Using the Central Limit Theorem, it is found that since the sample size is greater than 30, a normal approximation can be used, hence the test can be made.

<h3>Central Limit Theorem</h3>

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the sampling distribution is also approximately normal, as long as n is at least 30.

In this problem, the distribution of lengths is skewed, however, since the sample size is of 100 greater than 30, a normal approximation can be used, hence the test can be made.

To learn more about the Central Limit Theorem, you can check brainly.com/question/24663213

4 0

2 years ago

What are the golden ratio for percents?

tatyana61 [14]

I believe the answer is...
38.2%
50%
61.8%

7 0

4 years ago