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Bas_tet [7]
3 years ago
10

Empirical evidence suggests that 25% of Florida drivers are uninsured.

Mathematics
2 answers:
Nata [24]3 years ago
8 0
If the question is asking if only one isnt insured, the chances are 1/12.
If the question is asking if at least one isnt insured, the chances are 1/4.
abruzzese [7]3 years ago
5 0

Answer:

The probability is 0.2617

Step-by-step explanation:

The variable that said the number of drivers that are uninsured follow a binomial distribution, so the probability that x drivers are uninsured is calculated as:

P(x)=\frac{n!}{x!(n-x)!}*p^{x}*(1-p)^{n-x}

Where n is the number of drivers involved in an accident and p is the probability that any driver is uninsured, then:

P(x)=\frac{4!}{x!(4-x)!}*0.25^{x}*(1-0.25)^{4-x}

So, the probability that more than one of them are uninsured is:

P(x>1) = P(2) + P(3) + P(4)

Therefore, the values of P(2), P(3) and P(4) are:

P(2)=\frac{4!}{2!(4-2)!}*0.25^{2}*(1-0.25)^{4-2}=0.2109

P(3)=\frac{4!}{3!(4-3)!}*0.25^{3}*(1-0.25)^{4-3}=0.0469

P(x)=\frac{4!}{4!(4-4)!}*0.25^{4}*(1-0.25)^{4-4}=0.0039

Finally, the probability that more than one of them are uninsured is:

P(x>1) = 0.2109 + 0.0469 + 0.0039 = 0.2617

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NikAS [45]

Using the z-distribution, the test statistic is:

c) -2.63.

<h3>What are the hypothesis tested?</h3>

At the null hypothesis we test if the means are equal, equivalent to a subtraction of 0, hence:

H_0: \mu_D - \mu_C = 0

At the alternative hypothesis, we test if they are different, hence:

H_1: \mu_D - \mu_C \neq 0

<h3>What are the mean and the standard error for the distribution of differences?</h3>

For each sample, they are given as follows:

  • \mu_D = 12, s_D = \frac{5.2}{\sqrt{73}} = 0.6086.
  • \mu_C = 14, s_C = \frac{4.1}{\sqrt{81}} = 0.4556.

For the distribution of differences, it is given by:

  • \overline{x} = \mu_D - \mu_C = 12 - 14 = -2.
  • s = \sqrt{s_D^2 + s_C^2} = \sqrt{0.6086^2 + 0.4556^2} = 0.76

<h3>What is the test statistic?</h3>

The test statistic is given by:

z = \frac{\overline{x} - \mu}{s}

In which \mu = 0 is the value tested at the null hypothesis.

Hence:

z = \frac{\overline{x} - \mu}{s}

z = \frac{-2 - 0}{0.76}

z = -2.63.

More can be learned about the z-distribution at brainly.com/question/13873630

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