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Update SWIRTS DST post

Making my methodology and claims clearer.
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agude committed Oct 8, 2018
1 parent e4aeeda commit 1092c8ce001a946eb47ae07cc0c65324a1417a82
Showing with 13 additions and 7 deletions.
  1. +13 −7 _posts/2017-03-20-switrs_daylight_saving_time_accidents.md
@@ -49,13 +49,13 @@ choice for normalization because:

- The weeks after the time change have similar lighting to the week of the
time change.
- The accident rate is still elevated (as we shall see) a week later, so
normalizing by the very next week hides some of the increase that is due to
the start of DST.
- The accident rate is still slightly elevated a week later, so normalizing by
the very next week hides some of the increase that is due to the start of
DST.[^2]

The [violin plots][violin] below show the distribution of these ratios from
the years 2001 to 2016. A value greater than 1 means that there are more
accidents during the week when DST starts than the week after.
accidents during the week when DST starts than two weeks after.

[violin]: https://en.wikipedia.org/wiki/Violin_plot

@@ -67,8 +67,8 @@ after.][ratio_plot]][ratio_plot]

Except for Sunday, every day of the week following the time change has on
average a higher rate of accidents! I am surprised that the accident rate
stays high for so long. This indicates that it takes even longer than a week
for people to catch up on sleep and for the accident rate to go back to
stays high the entire week. This indicates that it takes even longer than a
week for people to catch up on sleep and for the accident rate to go back to
normal.

Daylight savings time causes more accidents, but those of us in California
@@ -81,7 +81,13 @@ all get that hour of sleep we deserve.

---

[^1]: It is also possible to use the week before or the week directly after to normalize. For the curious, I have also made [a plot using the week before for normalization][before_plot] and [the week after][after_plot]. They both show the same trend.
**Update**: I have rewritten part of this article to make my methodology
clearer.

[^1]: It is also possible to use the week before or the week directly after the DST change to normalize. For the curious, I have also made [a plot using the week before for normalization][before_plot] and [the week after][after_plot]. They both show the same trend.
[^2]: I assume that people are back to normal after three weeks, and so I use that week as a control. I then compare that ratios of the control week with [one week after the DST change][1_vs_3] and [two weeks after the DST change][2_vs_3] to see which is more normal. One week after has Monday and Thursday high, indicating people are still having more accidents than we expect. Two weeks after the ratios are near one, and so I conclude people are back to normal by then.

[before_plot]: {{ file_dir }}/accidents_after_dst_change_in_california_before.svg
[after_plot]: {{ file_dir }}/accidents_after_dst_change_in_california.svg
[1_vs_3]: {{ file_dir }}/accidents_one_and_three_weeks_after_dst_change_in_california.svg
[2_vs_3]: {{ file_dir }}/accidents_two_and_three_weeks_after_dst_change_in_california.svg

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