The point that will be on outlier in the table is (4, 55)
What is outlier?
An outlier is an observation or data point that lies an abnormal distance away from the other values in a random sample from a population.
An outlier is a data point that significantly differs from the rest of the data.
To identify a potential outlier, we use the interquartile range (IQR) and the concept of the 1.5 * IQR rule.
According to the problem we have the data
x: 0.5, 1, 1.5, 1.5, 2, 2.25, 2.75
y: 41, 35, 37, 36, 35, 30, 31
Calculate the IQR (Interquartile range) for Column 2
data set: 30, 31, 35, 35, 36, 37, 41
Q1 (the median of the lower half): 31
Q3 (the median of the upper half): 37
IQR = Q3 - Q1 = 37 - 31 = 6
Applying the 1.5 times the IQR rule
Lower Bound
= Q1 - 1.5 * IQR
= 31 - 1.5 * 6
= 22
Upper Bound
= Q3 + 1.5 * IQR}
= 37 + 1.5 * 6
= 46
Any data point outside this range may be considered a potential outlier.
Hence, point (4, 55) will be on outlier in the table.