Physical Laboratory for Mathematical Statistical Experiments (LMSE)
The Physical Laboratory for Mathematical Statistical Experiments (LMSE) emerged in Christchurch, New Zealand in 2009 as a cyber organisational response to various activities at the Christchurch Centre since 2007.
LMSE Christchurch Centre aims to facilitate activities that allow a deeper appreciation of Mathematics and Statistics for teaching/learning as well as research purposes. See current activities.
The laboratory facilitates teaching and learning styles that complement the traditional and predominant read-write style. A simple and concrete experiment may often allow the teacher/learner pair to kinesthetically and/or perceptually relate it to the mathematical model of the statistical experiment. Toward this goal LMSE Christchurch Centre has coordinated several projects listed below.
Increasingly, live and interactive lectures are facilitated using the Sage Notebook Server and Apache Spark, a fast and general engine for large-scale data processing via databricks to compute with datasets that won't fit in a single computer ("big data").
For a recent example of such lectures see the course on Monte Carlo Methods and Scalable Data Science.
See the publicly shared content and video lectures for these and other courses at:
- and for Scalable Data Science
- Computational Statistical Experiments in Matlab
- for Monte Carlo Methods
The activities and projects are supported by various funding bodies as detailed in the project reports. LMSE Christchurch Centre adheres to this Disclaimer Policy. Any one from anywhere is welcome to contribute and coordinate projects to legally share, remix and reuse under appropriate terms of Creative Commons.
The Laboratory has a long-term research focus on Trans-traditional Mathematical Statistical Experiments at the intersection of philosophical logic, rigorous machine-implementable mathematics and appropriate extensions of classical decision theory. Toward this focus, it currently aims to provide bench-marked data sets of mechatronically measurable non-linear systems to researchers interested in Hausdorff-extensions of classical statistical decision problems toward epistemologically valid experiments in the vein of Machine Interval Experiments: Accounting for the Physical Limits on Empirical and Numerical Resolutions.
Currently, most of the research emphasis is on highly integrative C++ class libraries for scientific and statistical computing. See codes and GitHub repositories at https://github.com/raazesh-sainudiin.
Projects Coordinated at The LMSE Christchurch Centre
projects that are hosted within the Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand:
A mechatronically measurable double pendulum that can produce nonlinear time series data
Estimating the Binomial probability p for a Galton’s Quincunx
Extending Galton’s binomial quincunx to the trinomial septcunx
Build Galton’s dice and draw samples from the Normal distribution
Testing the Approximation of pi by Buffon’s Needle Test
projects that are hosted within other institutions:
Honouring Pingala’s bijection between binary and natural numbers, binomial coefficients and Fibonacci numbers
Any enquiries to:
Last modified on Thursday, 10-Nov-2016 12:00:20 MST and served on Tuesday, 26-Sep-2017 14:46:04 MST.