In homes without working fire alarms, the chance of dying in a non-confined home fire is .0164 if there is a fire. In homes with working fire alarm, the chance of dying is .0115 if there is a fire.1 Similarly, the chance of a nonconfined house fire occurring is about 0.0015 (= 92,450/125,000,000). So, all else being equal, the chances of dying in your home due to a non-confined house fire are 0.000025 and 0.000017, respectively, without and with a fire alarm. Noting that smoke alarms range in price from $15 to $60 a piece, can we use this data and the trade-off method to estimate a range in the value of a statistical life? If so, what are these values? Do they seem reasonable? Please show all of your work and provide a raionale
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
In homes without working fire alarms, the chance of dying in a non-confined home fire is .0164 if there is a fire.
In homes with working fire alarm, the chance of dying is .0115 if there is a fire.1
Similarly, the chance of a nonconfined house fire occurring is about 0.0015 (= 92,450/125,000,000). So, all else being equal, the chances of
dying in your home due to a non-confined house fire are 0.000025 and 0.000017, respectively, without and with
a fire alarm.
Noting that smoke alarms
to estimate a range in the value of a statistical life? If so, what are these values? Do they seem reasonable?
Please show all of your work and provide a raionale
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