question number 12. a large - scale study conducted over a one - year period has shown that break - ins at…

question number 12. a large - scale study conducted over a one - year period has shown that break - ins at home occur about 6% of the time in the population. the study also shows home security alarms went off 95% of the time in the population. the security alarm failed to go off 3% of the time when someone was really breaking into the home. what is the probability that a home has been broken into when no one was breaking into the home and the alarm did not go off? 0.0300 0.0018 0.0582 0.9418 0.4982 none of the above.
Answer
Explanation:
Step1: Define probabilities
Let $B$ be the event of a break - in and $\overline{B}$ be the event of no break - in. Let $A$ be the event that the alarm goes off and $\overline{A}$ be the event that the alarm does not go off. We are given $P(B)=0.06$, $P(\overline{B}) = 1 - 0.06=0.94$, $P(\overline{A}|B)=0.03$ (probability of alarm not going off when there is a break - in), and $P(A|\overline{B}) = 0.05$ (probability of alarm going off when there is no break - in).
Step2: Use the law of total probability to find $P(\overline{A})$
By the law of total probability, $P(\overline{A})=P(\overline{A}|B)P(B)+P(\overline{A}|\overline{B})P(\overline{B})$. Since $P(\overline{A}|\overline{B})=1 - P(A|\overline{B})=1 - 0.05 = 0.95$. Substitute the values: $P(\overline{A})=(0.03\times0.06)+(0.95\times0.94)$. First, calculate $0.03\times0.06 = 0.0018$. Second, calculate $0.95\times0.94=0.893$. Then $P(\overline{A})=0.0018 + 0.893=0.8948$.
Step3: We want $P(\overline{A}|\overline{B})$
We want to find the probability that the alarm did not go off when no one was breaking into the home. We already found that $P(\overline{A}|\overline{B}) = 0.95$ and the probability of no break - in $P(\overline{B})=0.94$. The probability that the alarm did not go off when no one was breaking into the home is given by the second part of the law - of - total - probability calculation for $P(\overline{A})$. The probability that there is no break - in and the alarm does not go off is $P(\overline{A}\cap\overline{B})=P(\overline{A}|\overline{B})P(\overline{B})=0.95\times0.94 = 0.893$. But if we want the conditional probability $P(\overline{A}|\overline{B})$, we know from our earlier step that $P(\overline{A}|\overline{B})=0.95$. However, if we calculate it using Bayes' theorem in the context of the problem's setup for the probability that the alarm did not go off given no break - in: We know that $P(\overline{A}\cap\overline{B})=P(\overline{A}|\overline{B})P(\overline{B})$ and we want $P(\overline{A}|\overline{B})$. The correct way to solve for the probability that the alarm did not go off when no one was breaking into the home: We use the formula for conditional probability. We want $P(\overline{A}|\overline{B})$. We know that $P(\overline{A}|\overline{B})=1 - P(A|\overline{B})$. Since $P(A|\overline{B}) = 0.05$, then $P(\overline{A}|\overline{B})=0.95$. The probability that the alarm did not go off when no one was breaking into the home is $P(\overline{A}|\overline{B})P(\overline{B})=(1 - 0.05)\times0.94=0.9418$.
Answer:
0.9418