Answer:
18.67% probability that the sample proportion does not exceed 0.1
Step-by-step explanation:
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
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.
For the sampling distribution of a sample proportion, we have that [tex]\mu = p, \sigma = \sqrt{\frac{p(1-p)}{n}}[/tex]
In this problem, we have that:
[tex]\mu = 0.14, \sigma = \sqrt{\frac{0.14*0.86}{59}} = 0.045[/tex]
What is the probability that the sample proportion does not exceed 0.1
This is the pvalue of Z when X = 0.1. So
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
[tex]Z = \frac{0.1 - 0.14}{0.045}[/tex]
[tex]Z = -0.89[/tex]
[tex]Z = -0.89[/tex] has a pvalue of 0.1867
18.67% probability that the sample proportion does not exceed 0.1
