That Was the Week that Was: 2017 Week 05

That was the week that was TW3Hey, we’re only a day late (and a dollar short) this time.

We’re trying really hard to think of something clever to say here. That’s not cerebrospinal fluid in the vapor state coming out of our ears, it’s just steam.

The Boring Statistics

This week’s statistics were:

  • Posts: 28 posts — one extra (Saturday’s Breaking: Today’s “Refugees” Being Detained)
  • Word count:  about 16,800 (lower than usual).
  • Central Tendency Measures: Mean and median were low at 600 and 473. What does that mean? We’re writing shorter posts.
  • Posts below 100 words in length: 2. (See?)
  • Posts over 2,000: 2
  • Posts below 500: 15
  • Posts over 1000: 2

Significant milestones: None observed.

Traffic continues to be satisfactory. Too early to call February. January was not just a five-year January-over-January record, but also an all-time record with almost 270,000 uniques for the month.

Comments This Week

Comments: 619 as of 1700 Sunday. (Fewer than last week).

Most commented post: Monday’s Flying With a Gun, with 76.

Second most commented (i.e. runner-up) was Wednesday’s Year of the Pistol-Caliber Carbine? Really?, with 53 comments.

Thank you all for reading and commenting.

The Week in Posts

Here’s the recap of our posts for this week: (If the links are not live, they will be fleshed out later).

Going Forward

Well, we’re probably going to look at what a new SECDEF and new service secretaries mean to the military; we’re definitely going to have more straight dope on the HK433 and the German rifle competition; and we’ve got a great video Monday on what was probably the greatest reverse engineering exploit of all time. Plus, we promise we’ll think of something for the Wednesday Weapons Website of the Week, next week.

2 thoughts on “That Was the Week that Was: 2017 Week 05

  1. Mike_C

    First, welcome back. Thanks for all you do here, not least spending yesterday with a phone glued to your ear to get the GoDaddy issues resolved. The following humble ‘plaint was penned yesterday but stillborn. So here is zombie-infant ‘plaint:

    Posts below 100 words in length: 2. (See?)
    Posts over 2,000: 2
    Posts below 500: 15
    Posts over 1000: 2

    Rather than go and count myself, I’m just going to ask you.
    * You state two posts >2000, and two >1000. Do you mean: a) two posts >2000 and two other posts somewhere in the range of 1000 to 1999? Parenthetically, that would be [1000, 1999] or [1000, 2000) for those into notation esoterica. Or b) there are exactly two posts >2000 words, and since 2000 >1000, the >1000 thing just automatically followed? Sorry, but I can’t remember if you simply use 1000, 2000 etc as standard cutpoints for your metrics; if so that would explain much.
    * In the same vein, are the two <100 posts part of the fifteen that are <500 words?

    It will probably not come as a surprise that I'm taking a break from reviewing two manuscripts submitted for publication (to two different journals) and my head is in the nitpicking and resolve possible ambiguities phase. […] You'd be surprised how often people submit a supposedly scientific paper with a narrative part that is inconsistent with their data tables, or that the numbers don't add up within a single data table. "We examined 100 patients" says the narrative, but Table 1 says "Study Subjects: 50 men, 45 women" (and it's oppressive cis-sex binary either/or, no Baskin-Robbins 31 genders).
    Just had a thought. (It happens occasionally.) You track number of comments. How painful would it be to tabulate weekly word-count for comments? And I'd suggest a couple of sub-analyses. First, do longer posts tend to generate a) more comments, b) greater total comment-word count, or c) all of the above? Second, stratify #comments and total comment word-count by whether or not Kirk has weighed in on a particular post. Seriously. IOW, the underlying questions are: 1) does length of HN post predict comment WC and #? 2) Is +Kirk or no-Kirk an independent predictor of the same? (Note that this does not imply causation. If +Kirk means more comments, it simply may be that Kirk only comments on posts that are of greater overall interest. […] I actually don't believe that; I think his comments spur on other comments, but I'm trying to be all science-y here. To be even more properly science-y, the statistical analyses should take into account variables such as day of the week a given post appeared, and the category (topic listing) of each post, and doubtless other factors I have not yet thought of….)

    1. Hognose Post author

      Alas, I don’t believe the wordpress interface gives me comment word count. It would have to be manual, and that would be grim. In 2012, when I got excited if a post got 10 comments, it would have been too much work. Five years on, with dozens of comments routine? Ain’t doin’ it, don’t have will-work-for-food grad students for the grunt work.

      Those are interesting questions, though, and I’ve wondered the same thing.

      There’s probably some way to programmatically attack this with a perl module or something, but the juice isn’t worth the squeeze.

      See, some of the stuff I do with stats I do because it’s easy. And to answer your first question, I put the word counts into a column in Excel, and then apply several versions of this formula:
      With each one having a different “>” or “< " value (1000 in the example). Ergo, all the >2000 posts are counted also as >1000 posts; all the <100 posts are among the <500 posts. I could use value ranges instead of simple > operators, but these things just address my idle curiosity, mostly.

      I have not been very good at predicting what will lead to a lot of comments.

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