Traveling with friends and family, view from Green Lake towards Lake Tarawera, North Island, New Zealand. Time for walks, nice meals and setting R aside (although I have a few drafts for the blog soon to be published). Now back in the South Island we prepare for a great weekend with more walks, food and friends. Merry Christmas.
Author: Luis (Page 61 of 71)
I received an email from one of my students expressing deep frustration with a seemingly simple problem. He had a factor containing names of potato lines and wanted to set some levels to NA
. Using simple letters as example names he was baffled by the result of the following code:
lines <- factor(LETTERS) lines # [1] A B C D E F G H... # Levels: A B C D E F G H... linesNA <- ifelse(lines %in% c('C', 'G', 'P'), NA, lines) linesNA # [1] 1 2 NA 4 5 6 NA 8...
I think it is much more interesting to live with uncertainty than to live with answers that might be wrong.
—Richard Feynman in a TV interview.
After attending two one-day workshops last week I spent most days paying attention to (well, at least listening to) presentations in this biostatistics conference. Most presenters were R users—although Genstat, Matlab and SAS fans were also present and not once I heard “I can’t deal with the current size of my data sets”. However, there were some complaints about the speed of R, particularly when dealing with simulations or some genomic analyses.
I am not a statistician but I use statistics, teach statistics and write about applications of statistics in biological problems.
Last week I was in this biostatistics conference, talking with a Ph.D. student who was surprised about this situation because I didn’t have any statistical training. I corrected “any formal training”. On the first day one of the invited speakers was musing about the growing number of “amateurs” using statistics—many times wrongly—and about what biostatisticians could offer as professional value-adding. Yes, he was talking about people like me spoiling the party.
Continue reading