To find the first quartile (\(Q_1\)), we use the formula for the rank:
\[ \text{Rank} = Q \times (N + 1) \]
where \( Q = 0.25 \) and \( N = 15 \) (the number of data points).
\[ \text{Rank} = 0.25 \times (15 + 1) = 0.25 \times 16 = 4.0 \]
The quantile is at position 4 in the sorted data, which corresponds to the value 10.
Thus, the first quartile, \(Q_1\), is:
\[ \boxed{10} \]
To find the second quartile (\(Q_2\)), which is the median, we use the same formula for the rank:
\[ \text{Rank} = Q \times (N + 1) \]
where \( Q = 0.5 \).
\[ \text{Rank} = 0.5 \times (15 + 1) = 0.5 \times 16 = 8.0 \]
The quantile is at position 8 in the sorted data, which corresponds to the value 14.
Thus, the second quartile, \(Q_2\), is:
\[ \boxed{14} \]
To find the third quartile (\(Q_3\)), we use the same formula for the rank:
\[ \text{Rank} = Q \times (N + 1) \]
where \( Q = 0.75 \).
\[ \text{Rank} = 0.75 \times (15 + 1) = 0.75 \times 16 = 12.0 \]
The quantile is at position 12 in the sorted data, which corresponds to the value 20.
Thus, the third quartile, \(Q_3\), is:
\[ \boxed{20} \]
- The first quartile, \(Q_1\), is \( \boxed{10} \).
- The second quartile, \(Q_2\), is \( \boxed{14} \).
- The third quartile, \(Q_3\), is \( \boxed{20} \).