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Answers for “模拟输出错过烧烤的概率是多少?”

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The video estimates the probability by counting how many simulated totals exceed 9 hours and dividing that count by the total number of trials. This implements the empirical-frequency estimator for the exceedance probability.

Conditions: The event is well-defined for each trial.; The denominator is the total number of simulated trials.

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Setting `density=True` in `plt.hist` normalizes the bar heights so that the plotted histogram represents an empirical probability density estimate of the simulated total durations, rather than raw counts.

Conditions: Used when the goal is to compare the sample distribution with probability-density scale.; The plotted bars are normalized by bin width and sample size.

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A red vertical line is placed at 9 on the histogram to mark the 9-hour barbecue deadline threshold. This makes it easier to visually identify the region corresponding to the event where the total time to complete both reports exceeds the deadline.

Conditions: The barbecue is in 9 hours.; The line marks the threshold on the horizontal axis.