Question
Use the following information to answer questions 1-2.
A random variable is used to identify the number of students who attend live lessons in Statistics class for a semester.
X P(x)
6 0.08
7. 0.11
8 0.17
9 0.26
10 0.21
11 0.11
12 0.06
1. Does this table describe a probability distribution? What are the 2 requirements that must be met if it is a probability distribution?
2. What is the mean of the probability distribution in the table above?
A random variable is used to identify the number of students who attend live lessons in Statistics class for a semester.
X P(x)
6 0.08
7. 0.11
8 0.17
9 0.26
10 0.21
11 0.11
12 0.06
1. Does this table describe a probability distribution? What are the 2 requirements that must be met if it is a probability distribution?
2. What is the mean of the probability distribution in the table above?
Answers
Answered by
GPT-4o mini
1. To determine if the table describes a probability distribution, we need to check two requirements:
a. **Non-negativity**: The probabilities must be between 0 and 1, inclusive. In the provided table, all probabilities (P(x)) are positive and less than or equal to 1, which satisfies this requirement.
b. **Sum of probabilities**: The sum of all probabilities must equal 1.
Let's check the sum:
\[
0.08 + 0.11 + 0.17 + 0.26 + 0.21 + 0.11 + 0.06 = 1.00
\]
Since the sum equals 1, this requirement is also satisfied.
Therefore, the table does describe a probability distribution.
2. To find the mean (expected value) of the probability distribution, we use the formula:
\[
E(X) = \sum (X \cdot P(X))
\]
Now, we calculate the expected value using the values from the table:
\[
E(X) = (6 \cdot 0.08) + (7 \cdot 0.11) + (8 \cdot 0.17) + (9 \cdot 0.26) + (10 \cdot 0.21) + (11 \cdot 0.11) + (12 \cdot 0.06)
\]
Now calculating each term:
- \(6 \cdot 0.08 = 0.48\)
- \(7 \cdot 0.11 = 0.77\)
- \(8 \cdot 0.17 = 1.36\)
- \(9 \cdot 0.26 = 2.34\)
- \(10 \cdot 0.21 = 2.10\)
- \(11 \cdot 0.11 = 1.21\)
- \(12 \cdot 0.06 = 0.72\)
Now, summing these values:
\[
E(X) = 0.48 + 0.77 + 1.36 + 2.34 + 2.10 + 1.21 + 0.72 = 8.08
\]
Thus, the mean of the probability distribution is **8.08**.
a. **Non-negativity**: The probabilities must be between 0 and 1, inclusive. In the provided table, all probabilities (P(x)) are positive and less than or equal to 1, which satisfies this requirement.
b. **Sum of probabilities**: The sum of all probabilities must equal 1.
Let's check the sum:
\[
0.08 + 0.11 + 0.17 + 0.26 + 0.21 + 0.11 + 0.06 = 1.00
\]
Since the sum equals 1, this requirement is also satisfied.
Therefore, the table does describe a probability distribution.
2. To find the mean (expected value) of the probability distribution, we use the formula:
\[
E(X) = \sum (X \cdot P(X))
\]
Now, we calculate the expected value using the values from the table:
\[
E(X) = (6 \cdot 0.08) + (7 \cdot 0.11) + (8 \cdot 0.17) + (9 \cdot 0.26) + (10 \cdot 0.21) + (11 \cdot 0.11) + (12 \cdot 0.06)
\]
Now calculating each term:
- \(6 \cdot 0.08 = 0.48\)
- \(7 \cdot 0.11 = 0.77\)
- \(8 \cdot 0.17 = 1.36\)
- \(9 \cdot 0.26 = 2.34\)
- \(10 \cdot 0.21 = 2.10\)
- \(11 \cdot 0.11 = 1.21\)
- \(12 \cdot 0.06 = 0.72\)
Now, summing these values:
\[
E(X) = 0.48 + 0.77 + 1.36 + 2.34 + 2.10 + 1.21 + 0.72 = 8.08
\]
Thus, the mean of the probability distribution is **8.08**.
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