Users of my new online forecasting book have asked about having a facility for personal highlighting of selected sections, as students often do with print books. We have plans to make this a built-in part of the platform, but for now it is possible to do it using a simple browser extension. This approach allows any website to be highlighted, so is even more useful than if we only had the facility on OTexts.org. There are several possible tools available. One of the simplest tools that allows both highlighting and annotations is Diigo.
Posts Tagged ‘teaching’:
Earo Wang recently interviewed me for the Chinese website Capital of Statistics. The English transcript of the intervew is on Earo’s personal website. This is the third interview I’ve done in the last 18 months. The others were for: Data Mining Research. Republished in Amstat News. DecisionStats.
Hastie, Tibshirani and Friedman’s Elements of Statistical Learning first appeared in 2001 and is already a classic. It is my go-to book when I need a quick refresher on a machine learning algorithm. I like it because it is written using the language and perspective of statistics, and provides a very useful entry point into the literature of machine learning which has its own terminology for statistical concepts. A free downloadable pdf version is available on the website. Recently, a simpler related book appeared entitled Introduction to Statistical Learning with applications in R by James, Witten, Hastie and Tibshirani. It “is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences”. This would be a great textbook for our new 3rd year subject on Business Analytics. The R code is a welcome addition in showing how to implement the methods. Again, a free downloadable pdf version is available on the website. There is also a new, free book on Statistical foundations of machine learning by Böntempi and Ben Taieb available on the OTexts platform. This is more of a handbook and is written by two authors coming from a machine learning background. R code is also provided. Being an OTexts book, it is continually updated and revised, and is freely available
Last year I taught an online course on forecasting using R. The slides and exercise sheets are now available at www.otexts.org/fpp/resources/
I’ve been getting emails asking questions about my upcoming course on Forecasting using R. Here are some answers.
The publishing platform I set up for my forecasting book has now been extended to cover more books and greater functionality. Check it out at www.otexts.org.
The following video has been produced to advertise my upcoming course on Forecasting with R, run in partnership with Revolution Analytics.
I am teaming up with Revolution Analytics to teach an online course on forecasting with R. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and forecast evaluation techniques such as cross-validation. I will talk about some of my consulting experiences, and explain the tools in the forecast package for R. The course will run from 21 October to 4 December, for two hours each week. Participants can network and interact with other practitioners through an online community.
I’m speaking on this topic at the Young Statisticians Conference, 7–8 February 2013. If you’re a young statistician and live in Australia, please book in. It promises to be a great couple of days. Early registrations close on 2 January. Abstract for my talk: For 25 years I have been an intrepid statistical consultant, tackling the wild frontiers of real data, real problems and real time constraints. I have faced problems ranging from linguistics to river beds, from making paper plates to selling pies at the MCG, from tax office audits to surveys about the colour purple. University education helps prepare you to be a statistical consultant in the same way that Google maps helps prepare you to cross the Simpson Desert. You have some idea of the main features, but when you get there, nothing looks familiar. I will describe some of my adventures, and explain how to bluff your way through ignorance, work with inadequate tools, and deal with smelly clients. I will tell you the story of the client who wouldn’t give me the data, the client who wouldn’t tell me the problem, and the client who wanted all meetings held at random locations for security reasons. Along the way we will learn about the skills that
In many research universities, there can be a tension that arises when great teachers don’t publish much. I believe there is a place for excellent teachers who do limited research within a strong research university, but their contribution is considerably enhanced if they share their teaching insights. There are at least three reputable research journals for publishing articles on statistics education: Journal of Statistics Education Statistics Education Research Journal Technology Innovations in Statistics Education In addition, there is the less research-oriented (but certainly not less useful) Teaching Statistics.