Removing outliers in R with tools from dplyr and ggplot2 (CC232) 

Pat, This two-part exercise was probably my most favorite of those I have observed from you. I am currently in Northern Indiana so not suprisingly my data looks similar to yours. The data set I used went back to the early 1890s but there was a break in data collection from about 1910-1920 (World War I?). I did not see the extreme values in precip and snow that you observe. The most extreme precip and snow values were around 200 mm and 500 mm , respectively. When looking at the ten highest snow values I found events that line up with the big snow fall in Chicago in late January 1967. The station I am using may be experiencing higher precip (snow and rain) due to the lake effect. I am not sure how far or how large the lake effect is in Michigan in your neck of the woods. Finally, I converted the snow to rain using 1:12 ratio suggested by NOAA for this region. I thought it might be interesting to compare precip and "converted from snow precip". There are some 'hint' of a trend but caution is needed since the conversion of snow to precip is highly dependent on temperature.

Thanks!

I stumbled upon one of your videos few months back. My life is much easier since then. Your videos helped immensely in my work. Thank you!

Very intresting and useful, as always. What do you think about tests like dixon's test or Grubb's test to identify outliers ?

very useful

how about replacing outliers with NA instead of removing outliers? could you show me how?

Wouldn't it be worth imputing a median value to those outliers?

First 😝

Thanks!