To determine which observations are potentially influential, we calculate the leverage threshold using the formula: 3(k+1)/n

Given:

• k = 4 (independent variables)
• n = 100 (observations)

Threshold = 3(4 + 1)/100 = 3(5)/100 = 15/100 = 0.15

Observations with leverage measures above 0.15 are considered potentially influential:

• Observation 1: 0.03 < 0.15 (not influential)
• Observation 2: 0.25 > 0.15 (influential)
• Observation 3: 0.18 > 0.15 (influential)

However, the question asks which would "most likely" be considered influential. While both Observation 2 and Observation 3 exceed the threshold, Observation 2 has a much higher leverage (0.25) compared to Observation 3 (0.18), making it more clearly influential. In practice, observations with leverage significantly above the threshold are more likely to be flagged as influential.