Testing the hypothesis, it is found that since the p-value of the test is of 0.3015, which is greater than the significance level of 0.05, the data does not provide enough evidence to show that Alaska had a lower proportion of identity theft than 23%.
At the null hypothesis, we test if the proportion is of 23%, that is:
[tex]H_0: p = 0.23[/tex]
At the alternative hypothesis, we test if this proportion is lower than 23%, that is:
[tex]H_1: p < 0.23[/tex]
The test statistic is given by:
[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]
In which:
In this problem, the parameters are: [tex]p = 0.23, n = 1432, \overline{p} = \frac{321}{1432} = 0.2242[/tex]
Then, the value of the test statistic is:
[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]
[tex]z = \frac{0.2242 - 0.23}{\sqrt{\frac{0.23(0.77)}{1432}}}[/tex]
[tex]z = -0.52[/tex]
The p-value of the test is the probability of finding a sample proportion of 0.2242 or below, which is the p-value of z = -0.52.
Since the p-value of the test is of 0.3015, which is greater than the significance level of 0.05, the data does not provide enough evidence to show that Alaska had a lower proportion of identity theft than 23%.
A similar problem is given at https://brainly.com/question/14639462