Drag each tile to the correct box.

Victoria is an actuary for an insurance company. She recently compiled this table to help her determine health insurance premiums for the upcoming year. Consider the likeliness of each individual to have a need for health insurance. Order the individuals from least to greatest need for health insurance.

\begin{tabular}{|l|c|}
\hline
\multicolumn{1}{|c|}{Profile Description} & \begin{tabular}{c}
Probability of Visiting a Doctor \\
for Injury or Illness This Year
\end{tabular} \\
\hline
18-year-old male athlete & [tex]$16 \%$[/tex] \\
\hline
78-year-old male nonsmoker & [tex]$53 \%$[/tex] \\
\hline
65-year-old female smoker & [tex]$76 \%$[/tex] \\
\hline
26-year-old female nonsmoker & [tex]$14 \%$[/tex] \\
\hline
45-year-old male smoker & [tex]$39 \%$[/tex] \\
\hline
32-year-old female nonsmoker & [tex]$20 \%$[/tex] \\
\hline
\end{tabular}



Answer :

To determine the order of individuals from the least to the greatest need for health insurance based on their probability of visiting a doctor for injury or illness this year, we will start by listing the given probabilities:

- 26-year-old female nonsmoker: [tex]\(14 \% \)[/tex]
- 18-year-old male athlete: [tex]\(16 \% \)[/tex]
- 32-year-old female nonsmoker: [tex]\(20 \% \)[/tex]
- 45-year-old male smoker: [tex]\(39 \% \)[/tex]
- 78-year-old male nonsmoker: [tex]\(53 \% \)[/tex]
- 65-year-old female smoker: [tex]\(76 \% \)[/tex]

Now, let's organize these profiles in ascending order according to their probability:

1. 26-year-old female nonsmoker: [tex]\(14 \% \)[/tex]
2. 18-year-old male athlete: [tex]\(16 \% \)[/tex]
3. 32-year-old female nonsmoker: [tex]\(20 \% \)[/tex]
4. 45-year-old male smoker: [tex]\(39 \% \)[/tex]
5. 78-year-old male nonsmoker: [tex]\(53 \% \)[/tex]
6. 65-year-old female smoker: [tex]\(76 \% \)[/tex]

Thus, the final ordered list from the least to the greatest need for health insurance is:
1. 26-year-old female nonsmoker
2. 18-year-old male athlete
3. 32-year-old female nonsmoker
4. 45-year-old male smoker
5. 78-year-old male nonsmoker
6. 65-year-old female smoker