7 The discrete random variable X has probability distribution given by (4x +7) P(X= x) = for x= 1, 2, 3, 4. 68 (i) Find (a) E(X) (b) E(X²) (c) E(X²+5X– 2). (ii) Verify that E(X² + 5X– 2) = E(X²) + 5E(X) – 2.

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## Discrete Random Variable Probability Distribution

### Problem Statement
The discrete random variable \(X\) has a probability distribution given by:

\[ P(X = x) = \frac{4x + 7}{68} \quad \text{for} \; x = 1, 2, 3, 4. \]

### Questions
1. **Find:**
    1. **(a)** \( E(X) \)
    2. **(b)** \( E(X^2) \)
    3. **(c)** \( E(X^2 + 5X - 2) \)

2. **Verify** that:

\[ E(X^2 + 5X - 2) = E(X^2) + 5E(X) - 2. \]

### Explanation

1. **Expected Value (\( E(X) \)):**
The expected value, \( E(X) \), of a discrete random variable is the sum of the product of each possible value of the variable and its corresponding probability.

2. **Expected Value of \( X^2 \) ( \( E(X^2) \)):**
The expected value of \( X^2 \) is calculated by summing the products of each possible value squared, and its corresponding probability.

3. **Expected Value of the Expression ( \( E(X^2 + 5X - 2) \)):**
For a linear combination of expected values, the expected value of the combined expression can be separated into the sum of the expected values of each term, each appropriately weighted.

### Verifying the Formula:
To verify \( E(X^2 + 5X - 2) = E(X^2) + 5E(X) - 2 \), we can use the properties of expected values, which states that:

\[ E(aX + bY + c) = aE(X) + bE(Y) + c \]

where \(a\), \(b\), and \(c\) are constants and \(X\) and \(Y\) are random variables. This property can be used to simplify and verify the given expression.
Transcribed Image Text:## Discrete Random Variable Probability Distribution ### Problem Statement The discrete random variable \(X\) has a probability distribution given by: \[ P(X = x) = \frac{4x + 7}{68} \quad \text{for} \; x = 1, 2, 3, 4. \] ### Questions 1. **Find:** 1. **(a)** \( E(X) \) 2. **(b)** \( E(X^2) \) 3. **(c)** \( E(X^2 + 5X - 2) \) 2. **Verify** that: \[ E(X^2 + 5X - 2) = E(X^2) + 5E(X) - 2. \] ### Explanation 1. **Expected Value (\( E(X) \)):** The expected value, \( E(X) \), of a discrete random variable is the sum of the product of each possible value of the variable and its corresponding probability. 2. **Expected Value of \( X^2 \) ( \( E(X^2) \)):** The expected value of \( X^2 \) is calculated by summing the products of each possible value squared, and its corresponding probability. 3. **Expected Value of the Expression ( \( E(X^2 + 5X - 2) \)):** For a linear combination of expected values, the expected value of the combined expression can be separated into the sum of the expected values of each term, each appropriately weighted. ### Verifying the Formula: To verify \( E(X^2 + 5X - 2) = E(X^2) + 5E(X) - 2 \), we can use the properties of expected values, which states that: \[ E(aX + bY + c) = aE(X) + bE(Y) + c \] where \(a\), \(b\), and \(c\) are constants and \(X\) and \(Y\) are random variables. This property can be used to simplify and verify the given expression.
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