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The function [tex]$f(t)=349.2(0.98)^t$[/tex] models the relationship between [tex]$t$[/tex], the time an oven spends cooling, and the temperature of the oven.

Oven Cooling Time

[tex]\[
\begin{tabular}{|c|c|}
\hline
\begin{tabular}{c}
Time \\
(minutes) \\
$t$
\end{tabular} & \begin{tabular}{c}
Oven temperature \\
(degrees Fahrenheit) \\
$f(t)$
\end{tabular} \\
\hline
5 & 315 \\
\hline
10 & 285 \\
\hline
15 & 260 \\
\hline
20 & 235 \\
\hline
25 & 210 \\
\hline
\end{tabular}
\][/tex]

For which temperature will the model most accurately predict the time spent cooling?

A. 0
B. 100
C. 300
D. 400

Answer :

To solve this question, we need to determine which temperature most accurately matches the modeled prediction for a specific cooling time using the function [tex]\( f(t) = 349.2 \times (0.98)^t \)[/tex]. This function models the relationship between [tex]\( t \)[/tex], the time in minutes, and the oven temperature [tex]\( f(t) \)[/tex].

Here's how we can approach the solution step by step:

1. Calculate Temperature for Each Time: Use the given function to calculate the oven temperature for each of the cooling times provided (5, 10, 15, 20, and 25 minutes).

2. Compare Calculated Temperatures with Given Data: Compare the modeled temperatures for each time with the provided temperatures in the chart to determine how accurately the function predicts each measured temperature.

3. Identify Temperature With Smallest Difference: For each time, calculate the difference between the modeled temperature and the given temperature. The goal is to find the smallest difference, which indicates the most accurate prediction.

- At 5 minutes:
- Modeled: [tex]\( 349.2 \times (0.98)^5 \)[/tex]
- Given: 315°F

- At 10 minutes:
- Modeled: [tex]\( 349.2 \times (0.98)^{10} \)[/tex]
- Given: 285°F

- At 15 minutes:
- Modeled: [tex]\( 349.2 \times (0.98)^{15} \)[/tex]
- Given: 260°F

- At 20 minutes:
- Modeled: [tex]\( 349.2 \times (0.98)^{20} \)[/tex]
- Given: 235°F

- At 25 minutes:
- Modeled: [tex]\( 349.2 \times (0.98)^{25} \)[/tex]
- Given: 210°F

4. Conclusion: By calculating the differences, we find that the temperature prediction for 10 minutes (approximately 285.32°F) is the most accurate, closely matching the given temperature of 285°F.

Thus, the temperature for which the model most accurately predicts the time spent cooling is 285°F.

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