Category Archives: mathematics education

Why scientific measurements need to be adjusted

There is an excellent piece in Ars Technica about why scientific measurements need to be adjusted, and the implications of this for climate data. It is written by Scott K Johnson and is called “Thorough, not thoroughly fabricated: The truth … Continue reading

Posted in American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, AMETSOC, Berkeley Earth Surface Temperature project, Canettes Blues Band, citizen data, climate data, data science, environment, evidence, geophysics, GISTEMP, HadCRUT4, mathematics education, meteorological models, obfuscating data, open data, physics, science, spatial statistics, Tamino, the right to know, the tragedy of our present civilization, Variable Variability | Leave a comment

Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION: A Review

(Revised and updated Monday, 24th October 2016.) Weapons of Math Destruction, Cathy O’Neil, published by Crown Random House, 2016. This is a thoughtful and very approachable introduction and review to the societal and personal consequences of data mining, data science, … Continue reading

Posted in citizen data, citizen science, citizenship, civilization, compassion, complex systems, criminal justice, Daniel Kahneman, data science, deep recurrent neural networks, destructive economic development, economics, education, engineering, ethics, Google, ignorance, Joseph Schumpeter, life purpose, machine learning, Mathbabe, mathematics, mathematics education, maths, model comparison, model-free forecasting, numerical analysis, numerical software, open data, optimization, organizational failures, planning, politics, prediction, prediction markets, privacy, rationality, reason, reasonableness, risk, silly tech devices, smart data, sociology, Techno Utopias, testing, the value of financial assets, transparency | Leave a comment

Repaired R code for Markov spatial simulation of hurricane tracks from historical trajectories

I’m currently studying random walk and diffusion processes and their connections with random fields. I’m interested in this because at the core of dynamic linear models, Kalman filters, and state-space methods there is a random walk in a parameter space. … Continue reading

Posted in American Meteorological Association, American Statistical Association, AMETSOC, Arthur Charpentier, atmosphere, diffusion, diffusion processes, dynamic linear models, dynamical systems, environment, geophysics, hurricanes, Kalman filter, Kerry Emanuel, Lévy flights, Lorenz, Markov chain random fields, mathematics, mathematics education, maths, MCMC, mesh models, meteorological models, meteorology, model-free forecasting, Monte Carlo Statistical Methods, numerical analysis, numerical software, oceanography, open data, open source scientific software, physics, random walk processes, random walks, science, spatial statistics, state-space models, statistical dependence, statistics, stochastic algorithms, stochastics, time series | Leave a comment

“Holy crap – an actual book!”

Originally posted on mathbabe:
Yo, everyone! The final version of my book now exists, and I have exactly one copy! Here’s my editor, Amanda Cook, holding it yesterday when we met for beers: Here’s my son holding it: He’s offered…

Posted in American Association for the Advancement of Science, Buckminster Fuller, business, citizen science, citizenship, civilization, complex systems, confirmation bias, data science, data streams, deep recurrent neural networks, denial, economics, education, engineering, ethics, evidence, Internet, investing, life purpose, machine learning, mathematical publishing, mathematics, mathematics education, maths, moral leadership, multivariate statistics, numerical software, numerics, obfuscating data, organizational failures, politics, population biology, prediction, prediction markets, privacy, quantitative biology, quantitative ecology, rationality, reason, reasonableness, rhetoric, risk, Schnabel census, smart data, sociology, statistical dependence, statistics, the right to be and act stupid, the right to know, the value of financial assets, transparency, UU Humanists | Leave a comment

France, and Mathematics

Cédric Villani, does Mathematics. “Problems worthy of attack, prove their worth by hitting back.” — Piet Hein

Posted in abstraction, Google, mathematics, mathematics education, maths, networks, Pagerank, percolation theory, point pattern analysis, probability, rationality, reasonableness, stochastic algorithms | Leave a comment

On Smart Data

One of the things I find surprising, if not astonishing, is that in the rush to embrace Big Data, a lot of learning and statistical technique has been left apparently discarded along the way. I’m hardly the first to point … Continue reading

Posted in Akaike Information Criterion, Bayes, Bayesian, Bayesian inversion, big data, bigmemory package for R, changepoint detection, data science, data streams, dlm package, dynamic generalized linear models, dynamic linear models, dynamical systems, Generalize Additive Models, generalized linear models, information theoretic statistics, Kalman filter, linear algebra, logistic regression, machine learning, Markov Chain Monte Carlo, mathematics, mathematics education, maths, maximum likelihood, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical analysis, numerical software, numerics, quantitative biology, quantitative ecology, rationality, reasonableness, sampling, smart data, state-space models, statistical dependence, statistics, the right to know, time series | Leave a comment

Climate Denial Fails Pepsi Challenge

Originally posted on Climate Denial Crock of the Week:
Stephen Lewandowsky specializes in conducting research that pulls back the curtain climate denial psychology. He’s done it again. Washington Post: Researchers have designed an inventive test suggesting that the arguments commonly used…

Posted in American Association for the Advancement of Science, American Statistical Association, card draws, card games, chance, climate, climate change, climate data, climate education, confirmation bias, data science, denial, disingenuity, education, false advertising, fear uncertainty and doubt, fossil fuels, games of chance, geophysics, global warming, ignorance, mathematics, mathematics education, maths, obfuscating data, rationality, reasonableness, risk, science, science education, sociology, the right to know | Leave a comment

Of my favorite things …

(Clarifying language added 4 Apr 2016, 12:26 EDT.) I just watched an episode from the last season of Star Trek: The Next Generation entitled “Force of Nature.” As anyone who pays the least attention to this blog knows, opposing human … Continue reading

Posted in Anthropocene, bridge to somewhere, bucket list, Buckminster Fuller, Carl Sagan, climate, climate change, climate disruption, climate education, compassion, data science, Earle Wilson, ecology, Ecology Action, environment, evolution, geophysics, George Sughihara, global warming, Hyper Anthropocene, life purpose, mathematics, mathematics education, maths, numerical analysis, optimization, philosophy, physical materialism, physics, population biology, population dynamics, proud dad, quantitative biology, quantitative ecology, rationality, reasonableness, science, sociology, statistics, stochastic algorithms | 5 Comments

Causal Diagrams

Like Sankey diagrams, causal diagrams are a useful tool to assess and communicate complicated systems and their intrarelationships: It’s possible to use these for analysis and prescription: Here is the (promised) presentation on reenforcing loops: So how can these techniques … Continue reading

Posted in adaptation, bridge to nowhere, Carbon Cycle, carbon dioxide, carbon dioxide sequestration, Carbon Tax, Carbon Worshipers, causal diagrams, clean disruption, climate, climate change, climate disruption, climate education, climate models, demand-side solutions, differential equations, dynamical systems, ecology, economics, energy utilities, environment, exponential growth, fossil fuel divestment, fossil fuels, global warming, greenhouse gases, greenwashing, Hyper Anthropocene, mathematics, mathematics education, maths, methane, mitigation, natural gas, planning, prediction, rationality, reasonableness, recycling, Sankey diagram, sustainability, the right to know, zero carbon | Leave a comment

“Ignorance is not a cultural identity to celebrate. “

From meteorologist Dr Dan Satterfield, from his blog post, “The Real Reason U.S. SAT Test Scores Keep Dropping“: Far too many Americans just don’t think education is important. They may claim they do, but when a state gives 250 million … Continue reading

Posted in Carl Sagan, citizenship, civilization, Dan Satterfield, economics, education, humanism, ignorance, mathematics education, rationality, reasonableness, risk, science education, sociology, Susan Jacoby | Tagged , , | 1 Comment

Your future: Antarctica, in detail

Climate and geophysical accuracy demands fine modeling grids, and very large supercomputers. The best and biggest supercomputers have not been available for climate work, until recently. Watch how results differ if fine meshes and big supercomputers are used. Why haven’t … Continue reading

Posted in Antarctica, Anthropocene, bridge to nowhere, climate, climate change, climate disruption, climate zombies, disingenuity, ecology, ensembles, forecasting, geophysics, global warming, Hyper Anthropocene, ignorance, IPCC, Lawrence Berkeley National Laboratory, LBNL, living shorelines, mathematics, mathematics education, maths, mesh models, meteorology, multivariate statistics, numerical software, optimization, physics, rationality, reasonableness, risk, science, science education, sea level rise, spatial statistics, state-space models, statistics, stochastic algorithms, stochastics, supercomputers, temporal myopia, the right to know, thermodynamics, time series, University of California Berkeley, WAIS | Leave a comment

Solar installation progress, courtesy of MacSolarIndex.com

The MAC Solar Index tracks a set of solar manufacturing and installation companies. It is also the basis for the Guggenheim Investments “TAN” Exchange-Traded Fund (“ETF”, *). They recently published a progress report on global solar installations, which I wanted … Continue reading

Posted in adaptation, Anthropocene, carbon dioxide, citizen science, citizenship, civilization, clean disruption, climate, climate change, climate data, climate disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, destructive economic development, dynamic linear models, dynamical systems, ecology, economics, efficiency, energy, energy reduction, environment, exponential growth, forecasting, fossil fuel divestment, fossil fuels, geophysics, global warming, Hyper Anthropocene, investing, investment in wind and solar energy, mathematics, mathematics education, maths, meteorology, microgrids, open data, optimization, physics, politics, prediction, rationality, reasonableness, risk, science, science education, solar power, sustainability, the right to know, time series, Tony Seba, wind power, zero carbon | Leave a comment

CO2 experiment: fooling with Earth

Professor Richard D Schwartz wrote, in 2012, a nice article succinctly summarizing the scientific basis for climate change and global warming. Called “An astrophysicist looks at global warming”, he pithily summarized: “Greenhouse gas” warming occurs because the collisional de-excitation time … Continue reading

Posted in Anthropocene, astrophysics, bifurcations, bridge to nowhere, carbon dioxide, chance, citizenship, civilization, climate, climate change, climate disruption, climate education, dynamical systems, ecology, environment, forecasting, fossil fuels, games of chance, geophysics, global warming, ignorance, mathematics, mathematics education, maths, meteorology, oceanography, physics, Principles of Planetary Climate, rationality, Ray Pierrehumbert, reasonableness, science, science education, temporal myopia, the right to know | Leave a comment

Thank You

Originally posted on Open Mind:
To all the readers who make this blog worth writing: Thank you. Thank you for sharing my work. One of the things that makes me proud is that often my blog posts are used as…

Posted in astrophysics, citizen science, climate change, climate data, climate disruption, climate education, climate models, differential equations, dynamical systems, ecology, ensembles, forecasting, games of chance, geophysics, global warming, hiatus, Hyper Anthropocene, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, new forms of scientific peer review, open data, open source scientific software, physics, probabilistic programming, probability, rationality, reasonableness, reproducible research, risk, science, science education, spatial statistics, statistics, Tamino, the right to know, time series, transparency | Leave a comment

Desperate for a “Pause”

Originally posted on Open Mind:
When it comes to temperature at Earth’s surface, with 2014 the hottest year on record and 2015 on pace to exceed even that, things are getting hot for those who deny that global warming is…

Posted in climate, climate change, climate disruption, climate education, climate models, climate zombies, environment, geophysics, global warming, hiatus, mathematics, mathematics education, maths, meteorology, obfuscating data, open data, physics, rationality, reasonableness, reproducible research, science, science education, statistics, time series, Uncategorized | 1 Comment

Why decentralized electrical power has to win, no matter what Elon Musk says, and utilities are doomed

Image | Posted on by | 3 Comments

On the Climate Club

But if the other advanced nations had a stick — a tariff of 4 percent on the imports from countries not in the “climate club” — the cost-benefit calculation for the United States would flip. Not participating in the club … Continue reading

Quote | Posted on by | 2 Comments

The CWSLab workflow tool: an experiment in community code development

Originally posted on Dr Climate:
Give anyone working in the climate sciences half a chance and they’ll chew your ear off about CMIP5. It’s the largest climate modelling project ever conducted and formed the basis for much of the IPCC…

Posted in climate, climate education, climate models, computation, differential equations, dynamical systems, environment, forecasting, geophysics, global warming, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, NCAR, oceanography, open source scientific software, physics, Principles of Planetary Climate, Python 3, rationality, reasonableness, science, science education, state-space models, statistics, time series, transparency | Leave a comment

“… the most patronizing start to an answer I have ever received …”

Professor Christian Robert tries to help out a student of MCMC on Cross Validated and earns the comment that his help had “the most patronizing start to an answer I have ever received“. I learned a new term: primitivus petitor.

Posted in Bayes, Bayesian, mathematics, mathematics education, maths, MCMC, optimization, reasonableness, statistics, stochastic algorithms | Leave a comment

engineering and understanding with stable models

Stable distributions or Lévy -stable models is a class of probability distributions which contains the Gaussian, the Cauchy (or Lorentz), and the Lévy distribution. They are parameterized by an which is . Values of of 1 or less give distributions … Continue reading

Posted in approximate Bayesian computation, Bayesian, citizen science, climate, climate change, climate education, differential equations, diffusion processes, ecology, economics, forecasting, geophysics, information theoretic statistics, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, NOAA, oceanography, physics, rationality, reasonableness, risk, science, science education, stochastic search, the right to know | Leave a comment

The designers of our climate

Originally posted on …and Then There's Physics:
Okay, I finally succumbed and actually waded through some of the new paper by Monckton, Soon, Legates & Briggs called Why models run hot: results from an irreducibly simple climate model. I…

Posted in astrophysics, bridge to nowhere, carbon dioxide, carbon dioxide capture, carbon dioxide sequestration, Carbon Tax, Carl Sagan, citizenship, civilization, climate, climate change, climate education, differential equations, ecology, economics, engineering, environment, ethics, forecasting, fossil fuel divestment, geoengineering, geophysics, humanism, IPCC, mathematics, mathematics education, maths, meteorology, methane, NASA, NCAR, Neill deGrasse Tyson, NOAA, oceanography, open data, open source scientific software, physics, politics, population biology, Principles of Planetary Climate, probabilistic programming, R, rationality, reasonableness, reproducible research, risk, science, science education, scientific publishing, sociology, solar power, statistics, testing, the right to know | Leave a comment

It’s the Trend, Stupid

Originally posted on Open Mind:
Both NASA and NOAA report 2014 as the hottest year on record. Despite the new #1, neither the news itself nor the response to it has surprised me. The news that last year was so…

Posted in carbon dioxide, citizen science, climate, climate change, climate education, ecology, energy, environment, forecasting, geophysics, history, mathematics, mathematics education, maths, meteorology, NOAA, obfuscating data, physics, rationality, reasonableness, science, science education, statistics, Uncategorized | Leave a comment

Naomi Oreskes and significance testing

Naomi Oreskes has an op-ed in The New York Times today, which intends to defend the severe standards of evidence scientists employ, with special applicability to climate science and their explanation of causation (greenhouse gases produce radiative forcing), attribution (most … Continue reading

Posted in Bayes, Bayesian, citizen science, climate, climate education, mathematics, mathematics education, maths, model comparison, rationality, reasonableness, science, statistics, testing | Leave a comment

“[W]e want to model the process as we would simulate it.”

Professor Darren Wilkinson offers a pithy insight on how to go about constructing statistical models, notably hierarchical ones: “… we want to model the process as we would simulate it ….” This appears in his blog post One-way ANOVA with … Continue reading

Posted in approximate Bayesian computation, Bayes, Bayesian, biology, ecology, engineering, forecasting, mathematics, mathematics education, maths, model comparison, optimization, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, sociology, statistics, stochastic algorithms | Tagged | Leave a comment

climate internal variability is just residual variance from modeling with a smooth curve?

I happened across what I consider to be an amazing slide while “reading around” the work of Deser and colleagues. It is reproduced below, taken from Dagg and Wills: (Click image to see a larger picture, and use browser ‘back’ … Continue reading

Posted in cat1, citizen science, climate, climate education, forecasting, geophysics, mathematics, mathematics education, maths, meteorology, physics, rationality, reasonableness, science, statistics | 3 Comments

struggling with problems already partly solved by others

Climate modelers and models see as their frontier the problem of dealing with spontaneous dynamics in systems such as atmosphere or ocean which are not directly forced by boundary conditions such as radiative forcing due to increased greenhouse gas (“GHG”) … Continue reading

Posted in approximate Bayesian computation, Bayes, Bayesian, biology, climate, climate education, differential equations, ecology, engineering, environment, geophysics, IPCC, mathematics, mathematics education, meteorology, model comparison, NCAR, NOAA, oceanography, physics, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, statistics, stochastic algorithms, stochastic search | 1 Comment

Species abundances, raw abundances, and species composition

From Climate Change Ecology, An intuitive explanation for the 'double-zeroes' problem with Euclidean distances.

Posted in biology, climate, conservation, ecology, environment, mathematics, mathematics education, population biology, Schnabel census, science, science education, statistics | 3 Comments

Bayesian inference works even in a chaotic or deterministic world

Professor John Geweke, in a Comment on an article by Professor Mark Berliner a bit back (1992), shows how Bayesian inference continues to be a means for expressing subjective uncertainty even in a scheme where there are no stochastics but … Continue reading

Posted in Bayes, Bayesian, citizen science, economics, education, forecasting, mathematics, mathematics education, maths, rationality, reasonableness, statistics, stochastic algorithms | Leave a comment

Understanding mechanisms in climate over short periods and in local regions

This is interesting, because it shows how any particular observational history of Earth is one election of a large number of possible futures. This is exactly the same point made by Slava Kharin in his 2008 tutorial lecture “Statistical concepts … Continue reading

Posted in carbon dioxide, climate, climate education, differential equations, ecology, energy, environment, forecasting, geophysics, IPCC, mathematics, mathematics education, maths, meteorology, NCAR, NOAA, oceanography, physics, rationality, reasonableness, science, statistics, stochastic algorithms | 2 Comments

“Can we trust climate models?”

J. C. Hargreaves, J. D. Annan, “Can we trust climate models?”, WIREs Climate Change 2014, 5:435–440. doi: 10.1002/wcc.288. See also D. A. Stainforth, T. Aina, C. Christensen, M. Collins, N. Faull, D. J. Frame, J. A. Kettleborough, S. Knight, A. … Continue reading

Posted in Bayes, Bayesian, climate, climate education, differential equations, ecology, forecasting, geophysics, IPCC, mathematics education, meteorology, NCAR, NOAA, physics, rationality, reasonableness, risk, science, science education, statistics, stochastic algorithms | 1 Comment