What is the distribution of \( X \)?
Distribution of \( X \)
The age of students at George Washington Elementary School is uniformly distributed between 5 and 11 years old. Therefore, we can express this as:
\[
X \sim U(5, 11)
\]
\(\boxed{X \sim U(5, 11)}\)
What is the distribution of \( \bar{x} \)?
Distribution of \( \bar{x} \)
The mean of the uniform distribution is given by:
\[
\mu = \frac{a + b}{2} = \frac{5 + 11}{2} = 8.0
\]
The variance of the uniform distribution is:
\[
\sigma^2 = \frac{(b - a)^2}{12} = \frac{(11 - 5)^2}{12} = \frac{36}{12} = 3
\]
The variance of the sample mean \( \bar{x} \) is:
\[
\sigma^2_{\bar{x}} = \frac{\sigma^2}{n} = \frac{3}{37}
\]
Thus, the distribution of \( \bar{x} \) can be expressed as:
\[
\bar{x} \sim N\left(8.0, \frac{3}{37}\right)
\]
\(\boxed{\bar{x} \sim N\left(8.0, \frac{3}{37}\right)}\)
What is the probability that the average of 37 children will be between 7 and 7.5 years old?
Calculating the probability
To find the probability that the average age \( \bar{x} \) is between 7 and 7.5, we first calculate the cumulative distribution function (CDF) values at these points:
\[
P(7 < \bar{x} < 7.5) = P(\bar{x} \leq 7.5) - P(\bar{x} \leq 7)
\]
The calculated probability is:
\[
P(7 < \bar{x} < 7.5) = 0.0393
\]
\(\boxed{P(7 < \bar{x} < 7.5) = 0.0393}\)
The distribution of \( X \) is \( \boxed{X \sim U(5, 11)} \).
The distribution of \( \bar{x} \) is \( \boxed{\bar{x} \sim N\left(8.0, \frac{3}{37}\right)} \).
The probability that the average age is between 7 and 7.5 years is \( \boxed{0.0393} \).