1.0Probably Overthinking Ithttps://www.allendowney.com/blogAllenDowneyhttps://www.allendowney.com/blog/author/allendowney_6dbrc4/Small percentiles and missing data - Probably Overthinking Itrich600338<blockquote class="wp-embedded-content" data-secret="XfL2lQgDzK"><a href="https://www.allendowney.com/blog/2024/04/26/small-percentiles-and-missing-data/">Small percentiles and missing data</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.allendowney.com/blog/2024/04/26/small-percentiles-and-missing-data/embed/#?secret=XfL2lQgDzK" width="600" height="338" title="“Small percentiles and missing data” — Probably Overthinking It" data-secret="XfL2lQgDzK" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
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Here’s another installment in Data Q&A: Answering the real questions with Python. Previous installments are available from the Data Q&A landing page. low_percentile Bootstrapping percentiles¶ Here’s a question from the Reddit statistics forum. I’m trying to figure out how to determine the confidence interval for the .2 percentile temperature for specific set of observed temperatures (all hourly temperatures during January, February, and December since 2000). I have recordings for 53128 of the 53424 possible hourly recordings. How would I go... Read More Read More