To determine whether 74 inches is an outlier, we first need to understand the distribution of the players' heights after the replacement of the 71-inch tall player with the 73-inch tall player.
Assuming the rest of the team remains the same and that the heights of the players were, for example, similar to the original player heights (for instance, 71 inches, 72 inches, a few others, and the new 73 inches), we can analyze the data.
In the most basic context, an outlier is usually defined as a value that lies significantly outside the overall range of the data. This can often be determined by the interquartile range (IQR). However, if we don’t have the full distribution of the heights, we can infer from the general context.
Given the information:
- The replaced player is now 73 inches.
- If we assume the heights are in a reasonable range, a 74-inch player would be very close to the tallest player (if we had players of heights like 71, 73, etc.).
Thus, with these heights, 74 inches does not seem like a significant outlier since it is only 1 inch taller than the highest existing height (73 inches).
So, the best response would be:
No, 74 is not an outlier because it is not very different than the other heights in the data set.