State whether the function is a probability mass function or not. If not, explain why not. p={(9,0.9).(10,-0.4).(11,0.5)) Select all that apply. A. p is a probability mass function. B. p is not a probability mass function because it does not satisfy the third condition of probability mass functions.

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### Probability Mass Function Determination

**Question:**

State whether the function is a probability mass function or not. If not, explain why not.

Given function:
\[ p = \{(9, 0.9), (10, -0.4), (11, 0.5)\} \]

---

**Options:**

- [ ] **A.** \( p \) is a probability mass function.
- [ ] **B.** \( p \) is not a probability mass function because it does not satisfy the third condition of probability mass functions.
- [ ] **C.** \( p \) is not a probability mass function because it does not satisfy the second condition of probability mass functions.
- [ ] **D.** \( p \) is not a probability mass function because it does not satisfy the first condition of probability mass functions.

---

### Explanation:

A probability mass function (PMF) should satisfy the following conditions:
1. **Non-negativity:** Each probability \( p(x) \) must be greater than or equal to zero.
2. **Normalization:** The sum of all probabilities \( \sum p(x) \) must be equal to 1.
3. **Discrete values:** The function is defined for discrete values of the random variable.

For the given function \( p \):
- The pair (9, 0.9) assigns a probability of 0.9 to value 9.
- The pair (10, -0.4) assigns a probability of -0.4 to value 10.
- The pair (11, 0.5) assigns a probability of 0.5 to value 11.

To determine if \( p \) is a valid PMF, let's check these conditions:

1. **Non-negativity:** The probability assigned to the value 10 is -0.4, which is negative. This violates the first condition.
2. **Normalization:** The sum of probabilities is \( 0.9 + (-0.4) + 0.5 = 1.0 \). This satisfies the second condition.
3. **Discrete values:** The function is defined for discrete values, satisfying the third condition.

Since the first condition is not satisfied, \( p \) is not a probability mass function. Therefore, the correct answer is:

- [ ] A. \( p \) is a probability mass function.
- [ ] B. \( p \) is
Transcribed Image Text:### Probability Mass Function Determination **Question:** State whether the function is a probability mass function or not. If not, explain why not. Given function: \[ p = \{(9, 0.9), (10, -0.4), (11, 0.5)\} \] --- **Options:** - [ ] **A.** \( p \) is a probability mass function. - [ ] **B.** \( p \) is not a probability mass function because it does not satisfy the third condition of probability mass functions. - [ ] **C.** \( p \) is not a probability mass function because it does not satisfy the second condition of probability mass functions. - [ ] **D.** \( p \) is not a probability mass function because it does not satisfy the first condition of probability mass functions. --- ### Explanation: A probability mass function (PMF) should satisfy the following conditions: 1. **Non-negativity:** Each probability \( p(x) \) must be greater than or equal to zero. 2. **Normalization:** The sum of all probabilities \( \sum p(x) \) must be equal to 1. 3. **Discrete values:** The function is defined for discrete values of the random variable. For the given function \( p \): - The pair (9, 0.9) assigns a probability of 0.9 to value 9. - The pair (10, -0.4) assigns a probability of -0.4 to value 10. - The pair (11, 0.5) assigns a probability of 0.5 to value 11. To determine if \( p \) is a valid PMF, let's check these conditions: 1. **Non-negativity:** The probability assigned to the value 10 is -0.4, which is negative. This violates the first condition. 2. **Normalization:** The sum of probabilities is \( 0.9 + (-0.4) + 0.5 = 1.0 \). This satisfies the second condition. 3. **Discrete values:** The function is defined for discrete values, satisfying the third condition. Since the first condition is not satisfied, \( p \) is not a probability mass function. Therefore, the correct answer is: - [ ] A. \( p \) is a probability mass function. - [ ] B. \( p \) is
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