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Question: Suppose only \({\rm{75\% }}\) of all drivers in a certain state regularly wear a seat belt. A random sample of 500 drivers is selected. What is the probability that

a. Between 360 and 400 (inclusive) of the drivers in the sample regularly wear a seat belt?

b. Fewer than 400 of those in the sample regularly wear a seat belt?

Short Answer

Expert verified

(a) The probability that the number of drivers wearing seat belt lies between 360 and 400 is \({\rm{0}}{\rm{.9409}}\).

(b) The probability that the number of drivers wearing seat belt is less than 400 is \({\rm{0}}{\rm{.9943 }}{\rm{.}}\)

Step by step solution

01

Definition of Concept

Probability: Probability means possibility. It is a branch of mathematics which deals with the occurrence of a random event.

02

Find the probability that the number of drivers wearing seat belt lies between 360 and 400 

(a)

Considering the given information:

\(\begin{array}{c}{\rm{n = 500}}\\{\rm{p = 75\% }}\\{\rm{ = 0}}{\rm{.75}}\end{array}\)

The following are the requirements for a normal binomial distribution approximation:

As a result, the requirements are met, and we can use the normal distribution to approximate the binomial distribution.

The z-score is the value (using the continuity correction) multiplied by the standard deviation \(\sqrt {{\rm{npq}}} {\rm{ = }}\sqrt {{\rm{np(1 - p)}}} \) and divided by the mean np.

\(\begin{array}{c}z = \frac{{x - np}}{{\sqrt {np(1 - p)} }}\\ = \frac{{359.5 - 500(0.75)}}{{\sqrt {500(0.75)(1 - 0.75)} }} \approx - 1.60\\z = \frac{{x - np}}{{\sqrt {np(1 - p)} }}\\ = \frac{{400.5 - 500(0.75)}}{{\sqrt {500(0.75)(1 - 0.75)} }} \approx 2.63\end{array}\)

Using table A.3, calculate the corresponding normal probability:

\(\begin{array}{c}P(360 \le X \le 400) = P(359.5 < X < 400.5)\\ = P( - 1.60 < Z < 2.63)\\ = P(Z < 2.63) - P(Z < - 1.60)\\ = 0.9957 - 0.0548\\ = 0.9409\end{array}\)

Therefore, the required value is \({\rm{0}}{\rm{.9409}}\).

03

Find the probability that the number of drivers wearing seat belt is less than 400  

(b)

Considering the given information:

The z-score is the value (using the continuity correction) multiplied by the standard deviation \(\sqrt {{\rm{npq}}} {\rm{ = }}\sqrt {{\rm{np(1 - p)}}} \) and divided by the mean np.

\(\begin{array}{c}z = \frac{{x - np}}{{\sqrt {np(1 - p)} }}\\ = \frac{{399.5 - 500(0.75)}}{{\sqrt {500(0.75)(1 - 0.75)} }} \approx 2.53\end{array}\)

Using table A.3, calculate the corresponding normal probability:

\(\begin{array}{c}{\rm{P(X < 400) = P(X < 399}}{\rm{.5)}}\\{\rm{ = P(Z < 2}}{\rm{.53)}}\\{\rm{ = 0}}{\rm{.9943}}\end{array}\)

Therefore, the required value is \({\rm{0}}{\rm{.9943}}\).

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