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https://github.com/alexlee-gk/video_prediction/blob/master/scripts/plot_results.py#L25 In this line, I wonder why you use metric_se = np.std(metric, axis=0) / np.sqrt(len(metric)) instead of just standard deviation metric_se = np.std(metric, axis=0) ? Why is the standard deviation divided by np.sqrt(len(metric)?
metric_se = np.std(metric, axis=0) / np.sqrt(len(metric))
metric_se = np.std(metric, axis=0)
np.sqrt(len(metric)
The text was updated successfully, but these errors were encountered:
It's the standard error -- the more measurements you make, the more sure you are of the mean.
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Thank you, richzhang, I confused the standard deviation and the standard error, now I understand.
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https://github.com/alexlee-gk/video_prediction/blob/master/scripts/plot_results.py#L25
In this line, I wonder why you use
metric_se = np.std(metric, axis=0) / np.sqrt(len(metric))
instead of just standard deviationmetric_se = np.std(metric, axis=0)
? Why is the standard deviation divided bynp.sqrt(len(metric)
?The text was updated successfully, but these errors were encountered: