a phone buttery below as a random variable x with the The life of in hours Is Modeled probability density Runction: F(t) (t+2}3

A First Course in Probability (10th Edition)
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Chapter1: Combinatorial Analysis
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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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I need help with this probability density function problem. It asks to calculate the probability that the battery lasts longer than 1 hour. Please show work so that I can understand future problems like this.
### Understanding the Battery Life Model

The life of a phone battery in hours is modeled using a random variable \( X \). The probability density function (PDF) associated with this random variable is defined as follows:

\[
f(t) = 
\begin{cases} 
\frac{2}{(t+2)^3} & \text{for } t \geq 0 \\
0 & \text{for } t < 0 
\end{cases}
\]

#### Explanation of the Function

- **For \( t \geq 0 \):** The PDF is defined as \( \frac{2}{(t+2)^3} \). This implies that the probability of the battery life being any specific value \( t \) depends on this expression. The function decreases as \( t \) increases, indicating that longer battery life durations are less probable.

- **For \( t < 0 \):** The PDF is zero. This makes intuitive sense because negative time doesn't have a physical interpretation in this context, so the probability of a negative battery life is zero.

This PDF helps in understanding the likelihood of various battery life durations and is useful for statistical analysis and prediction of battery performance over time.
Transcribed Image Text:### Understanding the Battery Life Model The life of a phone battery in hours is modeled using a random variable \( X \). The probability density function (PDF) associated with this random variable is defined as follows: \[ f(t) = \begin{cases} \frac{2}{(t+2)^3} & \text{for } t \geq 0 \\ 0 & \text{for } t < 0 \end{cases} \] #### Explanation of the Function - **For \( t \geq 0 \):** The PDF is defined as \( \frac{2}{(t+2)^3} \). This implies that the probability of the battery life being any specific value \( t \) depends on this expression. The function decreases as \( t \) increases, indicating that longer battery life durations are less probable. - **For \( t < 0 \):** The PDF is zero. This makes intuitive sense because negative time doesn't have a physical interpretation in this context, so the probability of a negative battery life is zero. This PDF helps in understanding the likelihood of various battery life durations and is useful for statistical analysis and prediction of battery performance over time.
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PT=t=2t+23;           t0

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