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Read: David Falkayn: Star Trader

Reading Anderson’s Technic Civilization Sage makes you feel like a historian who tries to piece together the story of a society long gone by looking at a few personal accounts, by following the exploits, the fates and fortunes, of a few exceptional individuals. There are no records of ordinary persons.

You may get romantic notions of adventures, reckless and successful quests. And yet, Anderson manages to also show the dark(er) side, to hint at the fate of those left behind. That is quite an accomplishment. I still believe that not writing a unified tome (with multiple time lines, going back and forth), not putting everything in one book but having a collection of short stories and novellas is cause for how much better this work seems compared to other, more recent space operas.

The self-contained small(er) pieces are fun to read. You a read a story and you can put down the book feeling (entertained and) satisfied and rewarded. Reading never becomes chore, you do not have to read on so that something …anything happens! Instead a lot is happening in just a few pages. Of course, the frequent re-introductions of the protagonists are repetitive but some new facets are added to the characters every time and so you do not mind.

A final observation, though. While the physics (as far as you can expect from a science fiction novel) and economics seems sound (ok, this is not a textbook) I am not so sure about the armchair sociobiology that Anderson is feeding his readers. On the other hand, given that the short stories and novellas were written in the 60s and early 70s he was certainly was at the forefront of the idea that and how biological factors (like being a herbivore, carnivore, omnivore) determine individual social behavior and society. E. O. Wilson’s Sociobiology was only published in the mid-70s.

Read: Statistics Done Wrong

Reinhart’s Statistics Done Wrong is a refreshingly entertaining exposition of typical and embarrassingly widespread problems with the statistical analysis in (published) research.

It is not a textbook. It is non-technical. There are no formulas and only very few numbers. Nevertheless, it teaches the art of statistics. It may even instill the wish in the (un)initiated reader to pick up a statistics textbook and finally learn the stuff. As such it may be a good gift for a first year PhD researcher. Knowing about statistical power and related concepts before any data is collected can dramatically improve any research design and thus the final research (article).

There is nothing new in Statistics Done Wrong. All problems and all the examples chosen to illustrate them are already well known or were at least discussed in the usual blogs on applied statistics and data analysis. It is obvious that Reinhart follows, e. g., Andrew Gelman’s blog. Of course, he does. Everyone interested in the use and abuse, in good and bad practice of statistics follows (or should follow) Andrew’s blog. Nevertheless, Reinhart adds additional value. His writing is clear and accessible.

I have only one quibble: Reinhart states in the preface that he is not advocating any of the recent trends in and attempts to improve the practice of statistics: may this be the complete abandoning of p-values, the use of “new statistics” based on confidence intervals, or a switch to Bayesian methods. Actually, he is advocating rather strongly for the use of the “new statistics”. He advocates the use of effect size estimates and confidence intervals over vanilla p-values. This is absolutely fine. Yet, he should stand openly to this position and not deny it.

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Read: Generalized Linear Models for Categorical and Continuous Limited Dependent Variables

On first impression, the small textbook by Smithson and Merkle is a nice companion for Agresti’s Categorical Data Analysis and Analysis of Ordinal Categorical Data. It briefly discusses the theoretical foundation of the applied modelling approaches, explains the models using concrete examples, and provides a brief introduction to the relevant R (and Stata) functions.

On a more careful inspection, however, it becomes clear that the discussions are often too shallow. In particular the applied models would have benefited from more detail. The reader is referred to other textbooks for the missing details that would be necessary to really learn and understand why a certain approach should be taken and how to interpret and check any estimations. The text cannot stand alone. Its contribution is, thus, a mere cursory overview of a few select functions in R (and stata). Some additional functions for R are provided on a accompanying webpage. What, of course, begs the questions why the authors did not package these functions in an R library that is made available an the standard electronic archive for R, CRAN.

What really made me question the text, however, were phrases like: “…its p value is 0.057, which conventionally would not be regarded as not quite significant…”, and “This model is not quite significantly superior to the preceding one (… p=0.068).” This is not quite good scientific practice. In a textbook of all things.

Read: Maskerade

I do not like opera or musicals that much so I am sure I missed many puns reading Pratchett’s Maskerade. Or maybe not.

The witches make Maskerade a quite enjoyable and entertaining little book. I may have chuckled silently into myself a couple of times.

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Read: Busy

I may have read just too much of similar themed texts recently. Crabbe’s Busy seem utterly un-original. There is the usual mix of second hand research reporting and personal anecdotes to fill the gaps in support of an argument.

The list of references is impressive, admitted. Yet, mixing articles from highly respected authors in highly respected academic journals with pop-science books is less than inspiring confidence. The reliance on personal anecdotes adds to that impression.

On the other hand, the book’s thesis seems to be pretty much common wisdom nowadays. Many of the cited articles are ten or twenty years old. And thus, the gaps in the support of an argument may be not important at all. The conclusions are all accepted, there is nothing controversial.

This still leaves the entertainment value of the book. It reads quite nicely.

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