This is a very different book from my usual areas of forecasting and statistics. It is a personal memoir describing my journey of deconversion from Christianity.

Until a few years ago, I was regularly speaking at church conferences internationally, and my books are still used in Bible classes and Sunday Schools around the world. I even helped establish an innovative new church, which became a model for similar churches in other countries. Eventually I came to the view that I was mistaken, and that there was little or no evidence that the Bible was inspired or that God exists. In this book, I reflect on how I was fooled, and why I changed my mind.

Buy a print copy via CreateSpace
Buy a print copy via Amazon
Buy an e-copy via Google books

Advice to other journal editors

I get asked to review journal papers almost every day, and I have to say no to almost all of them. I know it is hard to find reviewers, but many of these requests indicate very lazy editors. So to all the editors out there looking for reviewers, here is some advice.

  1. Never ask someone who is an editor for another journal. I am handling about 500 submissions per year for the International Journal of Forecasting, and about 10 per year for the Journal of Statistical Software. There is very little time left to review for other journals. You are much better off identifying someone early in their career, within 10 years of finishing their PhD. They have more time, fewer requests, and are often looking to build an academic reputation.
  2. Look at the key papers cited in the submission, especially the recent ones, and then check the web sites of their authors. Find someone who is currently working in the area. For multi-authored papers, figure out which author was the PhD student, who was the professor, etc. If there was a post-doc involved, ask him/her.
  3. If that fails, do a Google Scholar search for an author who has written on the same topic recently. That is, in the last 2-3 years, not 10 years ago.
  4. If possible, ask someone who has recently authored a paper in your journal. They owe you one.
  5. Ask someone you know rather than a stranger. They are much more likely to say yes. If you don’t know many people you shouldn’t be an editor.

Mathematical annotations on R plots

I’ve always struggled with using plotmath via the expression function in R for adding mathematical notation to axes or legends. For some reason, the most obvious way to write something never seems to work for me and I end up using trial and error in a loop with far too many iterations.

So I am very happy to see the new latex2exp package available which translates LaTeX expressions into a form suitable for R graphs. This is going to save me time and frustration! Continue reading →

Data Science for Managers (short course)

I am teaching part of a short-course on Data Science for Managers from 10-12 October in Melbourne.

Course Overview

The impact of Data Science on modern business is second only to the introduction of computers. And yet, for many businesses the barrier of entry remains too high due to lack of knowhow, organisational inertia, difficulties in hiring the right manpower, an apparent need for upfront commitment, and more.

This course is designed to address these barriers, giving the necessary knowledge and skills to flesh out and manage Data Science functions within your organisation, taking the anxiety-factor out of the Big Data revolution and demonstrating how data-driven decision-making can be integrated into one’s organisation to harness existing advantages and to create new opportunities.

Assuming minimal prior knowledge, this course provides complete coverage of the key aspects, including data wrangling, modelling and analysis, predictive-, descriptive- and prescriptive-analytics, data management and curation, standards for data storage and analysis, the use of structured, semi-structured and unstructured data as well as of open public data, and the data-analytic value chain, all covered at a fundamental level.

More details available at it.monash.edu/data-science.

Early-bird bookings close in a few days.


The bias-variance decomposition

This week, I am teaching my Business Analytics class about the bias-variance trade-off. For some reason, the proof is not contained in either ESL or ISL, even though it is quite simple. I also discovered that the proof currently provided on Wikipedia makes little sense in places.

So I wrote my own for the class. It is longer than necessary to ensure there are no jumps that might confuse students.
Continue reading →

Murphy diagrams in R

At the recent International Symposium on Forecasting, held in Riverside, California, Tillman Gneiting gave a great talk on “Evaluating forecasts: why proper scoring rules and consistent scoring functions matter”. It will be the subject of an IJF invited paper in due course.

One of the things he talked about was the “Murphy diagram” for comparing forecasts, as proposed in Ehm et al (2015). Here’s how it works for comparing mean forecasts. Continue reading →

Keeping up to date with my research papers

Many people ask me to let them know when I write a new research paper. I can’t do that as there are too many people involved, and it is not scalable.

The solution is simple. Take your pick from the following options. Each is automatic and will let you know whenever I produce a new paper.

  1. Subscribe to the rss feed on my website using feedly or some other rss reader.
  2. Subscribe to new papers via email from feedburner.
  3. Go to my Google scholar page and click “Follow” at the top of the page.

The latter method will work for anyone with a Google scholar page. The Google scholar option only includes research papers. The first two methods also include any new seminars I give or new software packages I write.