Answer: One popular technique for locating outliers in a dataset is to utilize the interquartile range (IQR). The difference between the first (Q1) and third (Q3) quartiles is used to compute the internal rate of variation, or IQR. An outlier is any data point that is either above or below Q3 + 1.5 * IQR or Q1 - 1.5 * IQR. Let's first put the information in ascending order: $22, $48, $54, $64, $66, $73, and $78 Let's now compute Q1, Q3, and IQR: The median of the bottom half of the data set is Q1, or the first quartile: $48. The median of the top half of the data set is known as Q3, or the third quartile: $66. Q3 - Q1 = $66 - $48 = $18 is the IQR. We'll now establish the outlier thresholds: Lower limit: $48 (Q1 - 1.5 * IQR).($48 - $27 = $21) - 1.5 * $18 = $21. Upper bound: $66 + 1.5 * $18 = $66 + $27 = $93, or Q3 + 1.5 * IQR. An outlier is any data point that is greater than $93 or less than $21. $22 is the sole outlier in this dataset since it is below the lower bound.