a) Find the probability that the friend is between 5 and 25 minutes late b) it is 10 AM. There is a 30% probability the friend will arrive within how many minutes? a) The probability that the friend is between 5 and 25 minutes late is Type an integer or a decimal Round to three decimal places as needed) b) There is a 30% probability the friend will arrive within minutes. Type a whole number) 1 man 8 1/30- 10 20 30X Time 060

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**Understanding Uniform Probability Density Functions**

In this exercise, we'll explore the concept of a uniformly distributed random variable representing the lateness of a friend. We're given that the uniformly distributed variable \( X \) represents the lateness of this friend in minutes.

**(a) Calculating Probability Between Specific Intervals**

1. **Question (a):** Find the probability that the friend is between 5 and 25 minutes late.
   - **Input:** (Type an integer or a decimal. Round to three decimal places as needed.)

**(b) Finding the Time Interval for a Given Probability**

2. **Question (b):** It is 10 A.M. There is a 30% probability the friend will arrive within how many minutes?
   - **Input:** (Type a whole number.)

**Detailed Explanation of the Graph**

The graph depicted on the right is a uniform probability density function (PDF). The density function delineates a constant probability over a specified interval, indicating that an event is equally likely to occur at any point within this interval.

- **The x-axis:** Represents time (in minutes).
- **The y-axis:** Represents the density value.
- **Range on x-axis:** The interval is between 0 and 30 minutes.
- **Density value (y-axis):** Remains constant across the defined interval.
  - For a uniform distribution \(X \sim U(a, b)\), the probability density function \(f(x)\) is defined as:
    \[
    f(x) = \frac{1}{b - a} \quad \text{for} \quad a \leq x \leq b
    \]
  - In this case, \(a = 0\) and \(b = 30\), hence the density value \(f(x) = \frac{1}{30 - 0} = \frac{1}{30}\).
  - The graph displays a horizontal line at \(y = \frac{1}{30}\), from \(x = 0\) to \(x = 30\).

By working through these steps, students will learn to compute probabilities for uniform distributions and understand using probability density functions for practical time-related predictions.
Transcribed Image Text:**Understanding Uniform Probability Density Functions** In this exercise, we'll explore the concept of a uniformly distributed random variable representing the lateness of a friend. We're given that the uniformly distributed variable \( X \) represents the lateness of this friend in minutes. **(a) Calculating Probability Between Specific Intervals** 1. **Question (a):** Find the probability that the friend is between 5 and 25 minutes late. - **Input:** (Type an integer or a decimal. Round to three decimal places as needed.) **(b) Finding the Time Interval for a Given Probability** 2. **Question (b):** It is 10 A.M. There is a 30% probability the friend will arrive within how many minutes? - **Input:** (Type a whole number.) **Detailed Explanation of the Graph** The graph depicted on the right is a uniform probability density function (PDF). The density function delineates a constant probability over a specified interval, indicating that an event is equally likely to occur at any point within this interval. - **The x-axis:** Represents time (in minutes). - **The y-axis:** Represents the density value. - **Range on x-axis:** The interval is between 0 and 30 minutes. - **Density value (y-axis):** Remains constant across the defined interval. - For a uniform distribution \(X \sim U(a, b)\), the probability density function \(f(x)\) is defined as: \[ f(x) = \frac{1}{b - a} \quad \text{for} \quad a \leq x \leq b \] - In this case, \(a = 0\) and \(b = 30\), hence the density value \(f(x) = \frac{1}{30 - 0} = \frac{1}{30}\). - The graph displays a horizontal line at \(y = \frac{1}{30}\), from \(x = 0\) to \(x = 30\). By working through these steps, students will learn to compute probabilities for uniform distributions and understand using probability density functions for practical time-related predictions.
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