Polished statistical analysis chapters in evidence-based software engineering

November 24, 2018
By

(This article was first published on The Shape of Code » R, and kindly contributed to R-bloggers)

I have completed the polishing/correcting/fiddling of the eight statistical analysis related chapters of my evidence-based software engineering book, and an updated draft pdf is now available (download here).

The material was in much better shape than I recalled, after abandoning it to the world 2-years ago, to work on the software engineering chapters.

Changes include moving more figures into the margin (which is responsible for a lot of the reduction in page count), fixing grammatical typos, removing place-holders for statistical techniques that are unlikely to be of general interest to software engineers, and mostly minor shuffling around (the only big change was moving a lot of material from the Experiments chapter to the Statistics chapter).

There is still some work to be done, in places (most notably the section on surveys).

What next? My collection of data waiting to be analysed has been piling up, so I will spend the next month reducing the backlog.

The six chapters covering the major areas of software engineering need to be polished and fleshed out, from their current bare-bones state. All being well, this time next year a beta release will be ready.

While working on the statistical material, I have been making monthly updates to the pdf+data available. If it makes sense to do this for the rest of the material, then it will happen. I’m not going to write a blog post every month; perhaps a post after what look like important milestones.

As always, if you know of any interesting software engineering data, please tell me.

To leave a comment for the author, please follow the link and comment on their blog: The Shape of Code » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)