Mathematics, 26.03.2020 22:14, reneebrown017

The overhead reach distances of adult females are normally distributed with a mean of 195 cm and a standard deviation of 7.8 cm. a. Find the probability that an individual distance is greater than 204.30 cm. b. Find the probability that the mean for 15 randomly selected distances is greater than 193.70 cm. c. Why can the normal distribution be used in part (b), even though the sample size does not exceed 30? a. The probability is nothing. (Round to four decimal places as needed.) b. The probability is nothing. (Round to four decimal places as needed.) c. Choose the correct answer below. A. The normal distribution can be used because the mean is large. B. The normal distribution can be used because the finite population correction factor is small. C. The normal distribution can be used because the probability is less than 0.5 D. The normal distribution can be used because the original population has a normal distribution.

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answered: daya88

a) The probability is 0.1170

b) The probability is 0.7405

c) D. The normal distribution can be used because the original population has a normal distribution.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes 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 $s = \frac{\sigma}{\sqrt{n}}$ .