Category Archives: Probability and Bayesian analysis

The Election in Indi: #indivotes

This post on the election outcome in Indi is a little beyond my usual area of expertise, but it is a nice example of simple modelling. I’m going to tackle the question of whether Sophie Mirabella or Cathy McGowan will … Continue reading

Posted in Probability and Bayesian analysis | Tagged , , , , , , , , , , , , | 10 Comments

INTECOL talk, #INT13

I’m talking in the S11 Maths, Models & Methods session at INTECOL on Tuesday at 11:15 in room 4. The topic is “Developing biodiversity indices using models”. A copy of the slides is available here. I’ll also auto-tweet a little … Continue reading

Posted in CEED, Communication, Ecological indices, Probability and Bayesian analysis | Tagged , , , , , , , , , | 1 Comment

Statistical inference in ecology

Update: a pdf of an updated version of this chapter is available here. If this post had a single take-home message, it would be this: whatever statistical method you use, make sure that you use and report it appropriately. I’m … Continue reading

Posted in New research, Probability and Bayesian analysis | Tagged , , , , , , , , , , , , , , | 22 Comments

Considering uncertainty in environmental management decisions

This is a post about a new paper, which forms part of the PhD thesis of Yacov Salomon. Yacov is jointly enrolled in the School of Botany and the Department of Mathematics and Statistics at The University of Melbourne. Salomon, … Continue reading

Posted in Ecological models, New research, Probability and Bayesian analysis | Tagged , , , , , , , , , , , , , , , , | 2 Comments

Effects of timber harvesting on water yield from mountain ash forests

The effect of timber harvesting on water yield from mountain ash forest has been studied for decades. It is topical because mountain ash forests supply a large amount of water to Melbourne, a city of more than 4 million people. … Continue reading

Posted in Communication, Probability and Bayesian analysis | Tagged , , , , , , , , | 8 Comments

Planning for unplanned fires, and the response of biodiversity

There is a report in today’s Age about the decline of Leadbeater’s possum in the face of fires and timber harvesting. Professor David Lindenmayer of the Australian National University notes that the situation is dire, and that timber harvesting should … Continue reading

Posted in Communication, Probability and Bayesian analysis | Tagged , , , , | 3 Comments

Optimal monitoring when detectability varies – my talk at #ESAus2012

Edit: A paper based on this work has now been published in PLoS One (open access, i.e. free). doi: 10.1371/journal.pone.0115345. I’m looking forward to the Ecological Society of Australia conference this week. I’m speaking in the second time slot (2:15 … Continue reading

Posted in CEED, Communication, Detectability, Ecological models, New research, Probability and Bayesian analysis | Tagged , , , , , , , , , , , | 4 Comments

Detectability and traits of plants

If you’ve seen previous posts, you would realise that I am interested in the topic of imperfect detectability in field surveys. I’m interested in what influences detectability, how to account for it in analyses, and what it means when designing … Continue reading

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Nate Silver would be more of a guru if Romney wins Florida

Nate Silver is a prediction guru (or perhaps a witch). He compiles data from polling results, that he weights by sample size and measures of historical reliability, to predict the winner of the US presidential election. He calculates the probability … Continue reading

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Use confidence intervals to avoid the dance of the p-values

Geoff Cumming has written a great article in The Conversation about problems with using p-values for determining importance when using statistics. He recommends focusing on measuring effect sizes by using confidence intervals. It is well worth reading, but you should … Continue reading

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