The quartiles for the given dataset are as follows:
Q1 = 6 (25% of wait times are less than or equal to 6 minutes)
Q2 = 9 (50% of wait times are less than or equal to 9 minutes)
Q3 = 22 (75% of wait times are less than or equal to 22 minutes)
How to determine the quartiles from the data
To determine the quartiles, arrange the data in ascending order:
0, 0, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 8, 8, 9, 9, 9, 10, 10, 10, 12, 13, 14, 16, 16, 22, 22, 22, 26, 29, 30, 30, 32, 47, 54
There are 40 data points in the sample, so calculate the values of the quartiles:
Lower Quartile (Q₁):
Q₁ = (n + 1) / 4 = (40 + 1) / 4 = 10.25
Since Q₁ is not an integer, we can interpolate using the position formula:
Q₁ = Data[10] + 0.25 * (Data[11] - Data[10])
= 6 + 0.25 * (6 - 6)
= 6
Interpretation: The lower quartile (Q₁) is 6, which means that 25% of the wait times are less than or equal to 6 minutes.
Median (Q₂ / 50th percentile):
Since the data is already arranged in ascending order, the median is the middle value of the dataset.
Q₂ = Data[(n + 1) / 2] = Data[(40 + 1) / 2] = Data[20]
= 9
Interpretation: The median (Q₂) is 9, which means that 50% of the wait times are less than or equal to 9 minutes.
Upper Quartile (Q₃):
Q₃ = 3 * (n + 1) / 4 = 3 * (40 + 1) / 4 = 30.75
Since Q₃ is not an integer, interpolate using the position formula:
Q₃ = Data[30] + 0.75 * (Data[31] - Data[30])
= 22 + 0.75 * (22 - 22)
= 22
Interpretation: The upper quartile (Q₃) is 22, which means that 75% of the wait times are less than or equal to 22 minutes.
The accompanying data represent the wait time (in minutes) for a random sample of forty visitors to an amusement park ride. Complete parts (a) and (b). 7 14 4 6 5 30 6 6 22 9 7 47 10 10 30 0 26 6 9 5 22 8 22 9 29 16 54 3 10 32 0 4 7 13 3 7 5 12 8 16 (a) Determine and interpret the quartiles.