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Exercise

Visualize the Bootstrap

Continuing where we left off earlier in this lesson, let's visualize the bootstrap distribution of speeds estimated using bootstrap resampling, where we computed a least-squares fit to the slope for every sample to test the variation or uncertainty in our slope estimation.

To get you started, we've preloaded a function compute_resample_speeds(distances, times) to do the computation of generate the speed sample distribution.

Instructions

100 XP
  • Use the pre-defined compute_resample_speeds(distances, times) to compute the resample_speeds.
  • Use np.mean() to compute the speed_estimate from the resample_speeds.
  • Use np.percentile() with [5, 95] to compute the percentiles of resample_speeds, which define the confidence interval boundaries.
  • Use axis.hist() to plot the resample_speeds, specifying the bins with hist_bin_edges.
  • Using axis.axvline, specify the correct two indices of percentiles to mark the confidence interval boundaries on the chart.