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Koen Van de Moortel

Koen Van de Moortel
  • Master of Science
  • writer, programmer, private teacher & photographer at independent math & physics tutor

Open for challenges: do you have questions about measuring methodology, modeling, regression? Ask me! No cure, no pay.

About

13
Publications
28,792
Reads
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3
Citations
Introduction
Experimental physicist, looking for professional challenges. 2021: finished writing a book about measuring methodology and regression analysis + software, for students and teachers, in my native language: Dutch. See: book: www.lerenisplezant.be/metenisweten.htm software: www.lerenisplezant.be/fitting.htm If a publisher is interested, I can translate the book in English.
Current institution
independent math & physics tutor
Current position
  • writer, programmer, private teacher & photographer
Additional affiliations
January 1990 - June 2020
Many schools
Position
  • math/physics teacher
Education
September 1984 - June 1988
Ghent University
Field of study
  • Experimental physics

Publications

Publications (13)
Book
There are tons of books about measuring, regression analysis and mathematical modeling, but my focus is quite different. I will teach you: • The world cannot be described by linear models alone, absolutely not! There is a lot of beautiful other functions available! • Measurement errors should not be neglected. • Using common sense can make your...
Poster
Full-text available
Book about measuring and modeling, using ordinary and multidirectional regression analysis, for students, teachers, researchers, engineers...
Data
FittingKVdm 1.14 has been released! There are many software programs that do regression analysis (curve fitting), BUT only this one makes optimal use of the symmetry whenever dependent and independent variables can be switched! This will definitely improve your scientific modeling or calibration work! And in most cases it will estimate good initial...
Data
(European) shoe sizes of adults versus their height (126 men and 242 women, mostly from Belgium and Holland, Feb. 2023) - an educational example of my regression software "FittingKVdm".
Data
Software manual version 1.9, with more models and examples.
Method
Full-text available
Two methods for finding the "best" curve fitting through a set of data points are evaluated here: "multidirectional" and "ordinary" least squares regression (MDLS and OLS). The same artificial datasets with several amplitudes of generated noise were fed to both algorithms and the results were compared.
Method
Full-text available
This real life example shows why Multidirectional regression is better than the classical method (OLS): it treats the so-called independent and dependent variables equally.
Method
Full-text available
Does a person unconsciously improve his psychomotor while performing a simple task like throwing a pebble? Apparently he/she does, at least with our test person. The hypothesis was tested with 3 different methods: comparing averages, Kendall's tau, and regression.
Method
Full-text available
Regression analysis software manual with many real life examples from various sciences.
Preprint
Full-text available
The so-called 'least squares regression' for mathematical modeling is a widely used technique. It's so common that one might think nothing could be improved to the algorithm anymore. But it can. By minimizing the squares of the differences between measured and predicted values not only in the vertical, but also in the horizontal direction. I call t...
Method
Full-text available
The article shows an improvement for the well-known least squares regression analysis is possible in the case of invertible functions.
Method
Full-text available
For non-linear regression, often the logarithms of the variables are taken, to reduce the problem to a linear regression. With some examples, I explain you why this is not such a good idea.

Questions

Questions (3)
Question
Whenever I like an article in which regression analysis is used, I ask the authors if they can share some raw (!) data, because I'm writing a book and software about this topic, and I want to include very diverse real examples.
But, to my disappointment, practically nobody even reacts! Why?
Are people affraid that a new light on their data might disrupt their conclusions?
I thought openness was considered a virtue in the world of science?
But if I want to see articles that include data, I have to dig in the very old ones!
What are your thoughts?
P.S.: I can still use simple datasets from physics to psychology, from chemistry to sociology, anything...(just 1 independent variable, preferably with information about the measurement imprecision). Of course I quote you as the source. Thanks in advance!