Category Archives: Student t distribution

“Bayesian replication analysis” (by John Kruschke)

Posted on 1 September 2019 by

“… the ability to express [hypotheses] as distributions over parameters …” Bayesian estimation supersedes the t-test: (Also by Professor Kruschke.)

Posted in American Statistical Association, Bayesian, John Kruschke, model comparison, rationality, rhetorical statistics, statistical models, statistics, Student t distribution | Leave a comment

Dikran Marsupial’s excellent bit on hypothesis testing applied to climate, or how it should be applied, if at all

Posted on 30 May 2017 by

Frankly, I wish some geophysicists and climate scientists wrote more as if they thoroughly understood this, let alone deniers to try to discredit climate disruption. See “What does statistically significant actually mean?”. Of course, while statistical power of a test … Continue reading →

Posted in Anthropocene, anti-science, Bayesian, climate change, climate data, climate disruption, D. K. Marsupial, Frequentist, global warming, hiatus, Hyper Anthropocene, ignorance, John Kruschke, regime shifts, statistics, Student t distribution | Leave a comment

“Catching long tail distribution” (Ted Dunning)

Posted on 10 June 2016 by

One of the best presentations on what can happen if someone takes a naive approach to network data. It also highlights what is, to my mind, the greatly underappreciated t-distribution, which is typically only used in connection with frequentist Student … Continue reading →

Posted in Cauchy distribution, complex systems, data science, Lévy flights, leptokurtic, mathematics, maths, networks, physics, population biology, population dynamics, regime shifts, sampling, statistics, Student t distribution, time series | Leave a comment

p-values and hypothesis tests: the Bayesian(s) rule

Posted on 7 March 2016 by

The American Statistical Association of which I am a longtime member issued an important statement today which will hopefully move statistical practice in engineering and especially in the sciences away from the misleading practice of using p-values and hypothesis tests. … Continue reading →

Posted in approximate Bayesian computation, arXiv, Bayes, Bayesian, Bayesian inversion, bollocks, Christian Robert, climate, complex systems, data science, Frequentist, information theoretic statistics, likelihood-free, Markov Chain Monte Carlo, MCMC, Monte Carlo Statistical Methods, population biology, rationality, reasonableness, science, scientific publishing, statistical dependence, statistics, stochastics, Student t distribution | Leave a comment

Hansen et al.

Posted on 28 July 2015 by

Originally posted on Open Mind:
A new paper by Hansen et al., Ice melt, sea level rise and superstorms: evidence from paleoclimate data, climate modeling, and modern observations that 2 °C global warming is highly dangerous is currently under review…

Posted in adaptation, Antarctica, Anthropocene, Arctic, astrophysics, bifurcations, bridge to nowhere, carbon dioxide, carbon dioxide capture, Cauchy distribution, chance, civilization, climate, climate change, climate disruption, climate zombies, COP21, denial, differential equations, dynamical systems, ecology, economics, environment, ethics, floods, forecasting, games of chance, geophysics, global warming, Hyper Anthropocene, IPCC, James Hansen, mathematics, maths, meteorology, nor'easters, oceanography, physics, politics, probability, rationality, reasonableness, science, sea level rise, statistics, Student t distribution, Tamino, temporal myopia, the right to know, transparency, UNFCCC, zero carbon | Leave a comment

“Cauchy Distribution: Evil or Angel?” (from Xian)

Posted on 18 May 2015 by

Cauchy Distribution: Evil or Angel?. From Professor Christian Robert.

Posted in arXiv, Bayes, Bayesian, Cauchy distribution, information theoretic statistics, mathematics, maths, optimization, probabilistic programming, probability, rationality, reasonableness, statistics, stochastic algorithms, stochastics, Student t distribution | Leave a comment