2. The ages (to the nearest year) of students enrolled in a specific data analysis class have a cumulative probability distribution given by 17 18 19 20 21 22 23 0.60 0.83 0.92 1.00 F(x) 0 0.05 0.28 (a) Find the mean of X. (b) Find the standard deviation of X.

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### Problem 2: Analyzing Student Ages Using Cumulative Probability Distribution

The ages (to the nearest year) of students enrolled in a specific data analysis class have a cumulative probability distribution presented in the table below:

| \( x \) | 17  | 18  | 19  | 20  | 21  | 22  | 23  |
|--------|-----|-----|-----|-----|-----|-----|-----|
| \( F(x) \) | 0   | 0.05 | 0.28 | 0.60 | 0.83 | 0.92 | 1.00 |

#### Tasks:

(a) **Find the mean of \( X \):**

To find the mean, apply the formula for the mean of a discrete random variable using the cumulative distribution:

\[
\text{Mean} = \sum (x_i \cdot p_i)
\]

where \( p_i = F(x_i) - F(x_{i-1}) \).

(b) **Find the standard deviation of \( X \):**

First, calculate the variance using the formula:

\[
\text{Variance} = \sum (x_i^2 \cdot p_i) - (\text{Mean})^2
\]

where \( p_i = F(x_i) - F(x_{i-1}) \).

Finally, the standard deviation is the square root of the variance.
Transcribed Image Text:### Problem 2: Analyzing Student Ages Using Cumulative Probability Distribution The ages (to the nearest year) of students enrolled in a specific data analysis class have a cumulative probability distribution presented in the table below: | \( x \) | 17 | 18 | 19 | 20 | 21 | 22 | 23 | |--------|-----|-----|-----|-----|-----|-----|-----| | \( F(x) \) | 0 | 0.05 | 0.28 | 0.60 | 0.83 | 0.92 | 1.00 | #### Tasks: (a) **Find the mean of \( X \):** To find the mean, apply the formula for the mean of a discrete random variable using the cumulative distribution: \[ \text{Mean} = \sum (x_i \cdot p_i) \] where \( p_i = F(x_i) - F(x_{i-1}) \). (b) **Find the standard deviation of \( X \):** First, calculate the variance using the formula: \[ \text{Variance} = \sum (x_i^2 \cdot p_i) - (\text{Mean})^2 \] where \( p_i = F(x_i) - F(x_{i-1}) \). Finally, the standard deviation is the square root of the variance.
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