To determine whether the box plots support the inference that most of the tickets sold were about $40, we need to analyze the relevant details from the box plots for both ticket windows.
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Understanding Box Plots: A box plot displays the median, quartiles, and potential outliers of a dataset. It summarizes the distribution of a dataset. The key points to look for include:
- Median Line: The line inside the box represents the median ticket price, which indicates the middle of the data.
- Box Edges: The edges of the box represent the first quartile (Q1) and third quartile (Q3), showing where the middle 50% of the data lies.
- Whiskers: These extend to the minimum and maximum values (excluding outliers).
- Outliers: Points that fall outside the whiskers are typically plotted as individual points.
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Evaluating the Box Plot: To infer whether most ticket prices were approximately $40:
- Median Price: Check where the median line is positioned within the range of the box plot. If it is near $40, it supports the inference.
- Interquartile Range (IQR): If the IQR (the box itself) includes $40, this indicates that the majority of ticket prices were clustered around that value.
- Whiskers and Outliers: Review how many ticket sales occurred at high or low price points. If the whiskers extend significantly below or above $40 without high density around that price, this would weaken the inference.
If the box plot for the first window shows a median closer to $40 and a significant portion of the IQR surrounding that value, and if the range of prices and outliers do not drastically skew effects, then you could conclude there is support for the idea that most tickets sold were about $40.
However, without the actual box plot images or specific numerical data points, I can't definitively make that conclusion—analyzing the exact visual or numeric data is essential for a proper inference.