Statistics for journalists: A list of resources to improve your numeracy
A Spanish friend joked last week about how to keep her skin tanned for a wedding we’re attending in October.
Fortunately, I don’t have to worry about that, thanks to the final project in the MA in Data Journalism that I am finishing at Birmingham City University.
To help other journalists to catch up with statistics instead of worrying about their skins, I have gathered some of the materials that I revised this summer.
Back in June, I started reading what organisations such as the Royal Statistics Society and Science Media Centre have to say to journalists working with numbers. The result is a long list of short materials.
- Making sense of statistics. A guide to improve the questions we ask and how to avoid some pitfalls.
- Stories and statistics. These slides can be used for your personal development or workshops.
- A dozen rules of thumb for journalists. 12 questions to ask before reporting numbers.
- 10 best practice guidelines for reporting science & health stories. A short list to report in a balanced way.
- Making sense of uncertainty. An analysis about the role of uncertainty in science.
- Making sense of surveys. Five questions to ask when deciding whether to report a survey.
- Statistical pitfalls in the news. Slides from Maarten Lambrechts about common mistakes in media stories.
- Rock ‘n polls. Interactive explainer by Lambrechts to understand how polls work.
- A radio listener’s guide to ignore health stories. Kevin McConway and David Spiegelhalter developed a checklist to judge stories based on scientific health research.
- Statistics Every Writer Should Know. Robert Niles compiles eleven short guides about fundamental concepts.
In July, I rented a place in the library which became my second home until the middle of August. That may be the reason why my three pairs of sandals and my lovely summer dresses have been useless during the “best English summer I’ve ever had,” as my British friend described it, while my German and Polish friends complained that it was “too hot to be outside”.
So, making the most of the air condition in the library, I took these courses:
- Statistics for journalists. A basic course of 30 minutes carried out by the Royal Statistics Society.
- Bulletproof Data Journalism. A three-hour ‘class’ taught by Stijn Debrouwere which covers the risk of confounders, cherry-picking and other flaws of the data.
- Foundations of Data Analysis. A 20 hours course taught by Dr Mahometa from Austin University about descriptive methods in R.
- Statistics foundations 1, 2 and 3. A three-part course by Eddie Davila which goes from basic statistics to intermediate and advanced levels. It covers descriptive methods and inferential statistics.
- Introduction to probability and data. Mine Çetinkaya-Rundel from Duke University guides this course which introduces you to inferential methods and probability.
I have accompanied them with some readings. The first three are the ones I liked the most.
- The tiger that isn’t: Seeing through a world of numbers, by Michael Blastland and Andrew Dilnot.
- Naked Statistics: Stripping the dread from the data, by Charles Wheelan
- Bad Science, by Ben Goldacre.
- How to read a paper: The basic of evidence-based medicine, by Trisha Greenhalgh.
- How to lie with statistics, by Darren Huff.
- The new precision journalism, by Phillip Meyer.
- A mathematician reads the newspaper, by John Allen Paulos.
- Working with numbers and statistics: A handbook for journalists, by Charles Livingston and Paul Voakes.
- Statistical inference for everyone, by Brain Blais.
This list provided me with robust knowledge in statistics, and it also laid the foundations for successful understanding of more technical material not written for journalists.
But the more I dug into statistics, the more resources I found. And at the end of August I have added to my ‘to-do-after-MA’ list the following books:
- Numbers rule your world: The hidden influence of probability and statistics on everything you do, by Kaiser Fung.
- The elements of statistical learning, by Trevor Hastie, Robert Tibshirani, and Jerome Friedman.
- Think stats: Exploratory data analysis in Python, by Allen B. Downey.
The good news is that the summer has not ended everywhere and I will start some of these books while lying on the beach because the wedding of October is in the Canary Islands.
I concluded the MA with a very successful result, but that does not mean my approach to statistics has ended. I have less time, but still reading and digging into it.
Here I’ll list new resources I find interesting.
- A guide to statistics for journalists. The Reuters Institute organised a webinar with Denise Lievesley, former director of Statistics at UNESCO and Principal of Green Templeton College, University of Oxford.
- The art of statistics: Learning from data, the new book by David Spiegelhalter. I’ve just received the book, but I’ve been following his Medium blog for a while. So, my expectations are quite high.
- Factfulness: Why things are better than you think, by Hans Rosling. I found this basic but essential with a couple of tips about comparison, longer trends, the 80–20 rule and biases.
Any other recommendation? Please, add it here!