Go read Sarah Hoyt

Chatty stuff about writing indie SciFi, with snarky political and cultural commentary.  Oh, and a great geeky sense of humor:

SchrodingerRevenge

Update:  Francis turner says that cat complains too much

ACHTUNG SPERRFRIST 30.12.2013 Feuer-Biga #17

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Science is getting exciting!

Five very interesting articles recently popped up on the web, suggesting that current science is much more interesting than the average Joe might think:

    • At FiveThirtyEight*, Christie Aschwanden’s Science Isn’t Broken gives a great exposition on scientific fraud, p-hacking, and why science is much more difficult than most folks realize.
    • Robert Matthews, writing in UAE’s The National, says Lone researchers with radical ideas may hold the keys to science’s unanswered questions.  One of those “loners” is “Eleonora Troja, an astronomer at NASA’s Goddard Space Flight Center who studies X-rays, had hoped for years to detect the light from a neutron-star merger, but many people thought she was dreaming.”  
    • FiveThirtyEight’s Rebecca Boyle,  in Two Stars Slammed Into Each Other And Solved Half Of Astronomy’s Problems. What Comes Next?, describes that dream coming true and a revolution in astronomy that occurred in just 3 weeks this past August.
    • In The Serial-Killer Detector, the New Yorker’s Alec Wilkinson tells the story of Thomas Hargrove’s one-man Big Data project to categorize and analyze murders in the United States (751,785 since 1976) with the goal of tracking down serial killers.  From the description, is appears Hargrove has done yeoman’s work combining Small N and Big Data techniques with great success. “Hargrove thinks … that there are probably around two thousand serial killers at large in the U.S.”  Yikes!
    • Want to get in on the action?  At ScienceAlert.com, Mike McRae tells how Now You Can Build Your Very Own Muon Detector For Less Than $100, and possibly contribute to a Big Data project supporting stellar astronomy.

*ESPN’s website that analyzes sport statistics, election polling, and (apparently) anything else that catches their analysts’ eyes.

 

Artichoke and Shellfish Soup

So I was suddenly confronted with a windfall of canned shellfish when our local WalMart Neighborhood store closed this month.  I decided to get even more serious about recipes based on McIntosh’s Tin Fish Gourmet.  She gives a simple recipe for Oyster and Artichoke Stew, which I embellished beyond all recognition into this rich, creamy (and low-carb) soup:

  • 1 carrot, thinly sliced
  • 1 celery rib, thinly sliced
  • 1/4 red onion, thinly sliced
  • 1 can artichoke hearts, halved
  • 2 tbsp cooking oil
  • 2 oz butter
  • 1/4 cup flour
  • 1 cup milk
  • 1/4 cup sour cream
  • 1 or 2 tins of diced clams, smoked oysters, mussels, or whatever
  • 3 green onions, thinly sliced
  • 1 large avocado, quartered and (you guessed it) thinly sliced

Saute the carrot, celery, and red onion slices in oil until the onion is transparent, then add the artichoke hearts, reserving the liquid for a bit later.  When everything is nicely sauteed, set these vegetables aside.  Add the butter and flour to the pan, and whisk into a roux.  When the roux is bubbling and starting to darken, add the liquid from the artichoke hearts and any liquid from the tinned shellfish to make a sauce.  Once it comes to a boil, add the sour cream and enough milk to get a creamy soup consistency.  Add the sauteed vegetables and the shellfish, and bring to a boil.  Then turn off the heat.

Serve in shallow soup dishes, topped with 3 or 4 slices of avocado and some of the green onion.  This cries out for a dry white wine on the side.

 

When all you have is a hammer…

…everything looks like a nail.

Daniel Lakens, the 20% Statistician, takes a rare but easy shot at statisticians and null hypothesis significance testing.

Our statistics education turns a blind eye to training people how to ask a good question. After a brief explanation of what a mean is, and a pit-stop at the normal distribution, we jump through as many tests as we can fit in the number of weeks we are teaching. We are training students to perform tests, but not to ask questions

He defines

…the Statisticians’ Fallacy: Statisticians who tell you ‘what you really want to know’, instead of explaining how to ask one specific kind of question from your data.

My favorite is the two-tailed test of the difference of two means, which can provide evidence that the two are different, but not that they are (nearly) the same.  My runners up are goodness-of-fit tests, which do no such thing.  Sometimes I feel like I’m selling the researcher’s version of Snake Oil, rather than teaching sound data analysis and interpretation.

Lakens closes with an excellent addendum, a reference to David Hand’s Deconstructing Statistical Questions,  which goes into much more detail.

A Tinned Oyster Treat

Some time ago, I promised I’d report on my attempts at recipes from Barbara-Jo McIntosh’s Tin Fish Gourmet.  As usual, I didn’t read the cookbook so much as fixed recipes, but as more of a guide.  So I combined elements from two different recipes, “Christmas Eve Oysters” (p 82) and “Shrimp and Spinach-Stuffed Tomatoes” (p 133).  The result is delicious.

TinFishGourmet

So here’s my first offering: Oyster-Stuffed Tomatoes.

  • 8 Campari tomatoes
  • one mushroom
  • one green onion
  • one tablespoon capers
  • 1/4 cup grated parmesan cheese
  • one 3 1/2 oz can smoked oysters

With a paring knife, cut off the tops of the tomatoes, removing the stem.  Then use a melon baller to scoop out most of the flesh of the tomatoes (save this for your soup or sauce stock).  Dice the mushroom to pea size, and slice the green onion finely.  Mix mushroom, onion, capers, cheese, and oysters in a bowl, using the oil from the tinned oysters to moisten the mixture.  Spoon mixture into the tomatoes.  Place stuffed tomatoes in a shallow, foil-lined pan, and broil for 10 minutes.  Serve immediately.

My wife’s only complaint was that the tomatoes should have been bigger, with more stuffing.

 

Seven Pillars

Wisdom hath built her house, she hath hewn out her seven pillars.  –Proverbs 9:1

I just finished Stephen Stigler’s The Seven Pillars of Statistical Wisdom, and I’m daunted–and embarrassed that I waited so long to read it.  Stigler gives us a structure and taxonomy to statistical thinking* that gives us the “big picture” of statistics.

StiglerSevenPillars

Quite a difference from the descriptives-to-inference-to-models approach that most textbook authors follow.  This is making me rethink how I approach my introductory courses, especially those for statistics majors.  I’m starting with a baby step: adding the (inexpensive, paperbound) book as a required reading in my statistical research methods class.

*the 7 pillars: aggregation, information, likelihood, intercomparison, regression, design, and residual (and that’s just the table of contents!)

Deus ex Machina, on steroids

…is the tagline I’d use to describe Stephen Baxter and Alastair Reynolds’ The Medusa Chronicles, the startling sequel to Arthur C. Clarke’s short story “A Meeting with Medusa.”

TheMedusaChronicles

Baxter and Reynolds are up to their usual tricks of piling wonder atop wonder in their usual over-the-top scenarios, while cleverly maintaining Clarke’s style and tone, AND sneaking in episodes strongly reminiscent of 2001, A Space Odyssey.  An added bonus is the introduction of a “new physics” based on the Mach Principle, which is still puzzling serious researchers today.

…local physical laws must be shaped by the large-scale structures of the universe.  And it is meaningless to talk of the behaviour of an object in isolation, without relation to the rest of the universe.  This was 90’s insight.  From that beginning, 90, and a group of others, developed a new kind of physics–from first principles, based only on observation and philosophy.  (The Medusa Chronicles, p. 99)