What is the use of
statistics in science?
This is a good question, that came on my Quora feed. I would say that essentially every
present-day science uses statistical techniques as a key process in exploratory
research and theory confirmation, to a greater or lesser extent (usually
greater).
Sometimes these are traditional statistical methods, other
times they are newer “data science” techniques such as machine learning (most
of these algorithms draw upon statistical and probabilistic concepts). The statistical modelling methods are often
better for inference (understanding what is going on), while machine learning
methods are often better at prediction or categorization. That’s not a hard and fast rule, but a useful
generalization, I think.
As a general statement, pretty well all lab sciences depend
on statistical methods for error analysis.
The ideas behind hypothesis testing and confidence intervals are also
ubiquitous in physical, medical and social sciences.
Here are some more specific examples.
·
Physics:
If you take a physics degree, you are likely to come to a course called
“Statistical Physics” or words to that effect.
So, that tells you something right there. Here are a few other examples, and not at all
an exhaustive list.
o
A lot of thermodynamics has a heavy statistical
focus (e.g. temperature is explained as the average kinetic energy of a large
ensemble of molecules).
o
Geophysics leans very heavily on statistical
theory, especially time series analysis (e.g. I took a course called “Time
Series Analysis in Geophysics”). Very
useful in exploration geophysics and earthquake analysis.
o
Astrophysics makes extensive use of statistics
in analysis of stellar spectra (e.g. Power spectrum analysis helps to find
planets in other solar systems). A lot
of error analysis was developed for astronomical observations in earlier
centuries.
o
Particle physics makes use of statistical
techniques to establish whether a new particle has actually been discovered
(e.g. you hear things like “it is a 3 sigma event” when reports from particle
accelerators are discussed).
·
Geology
and Earth Sciences: This makes use of statistics for many reasons:
o
Geophysical methods as outlined above.
o
Methods for estimating ore reserves or petroleum
deposits depend heavily on sampling theory.
·
Biological
Sciences: Lots of statistical techniques used here as well:
o
Population genetics makes use of many
statistical methods, such as cluster analysis to make taxonomical decisions.
o
Molecular genetics (e.g. the big GWAS studies
about human evolution) uses statistical methods, such as regression (whether
via statistical methods or machine learning methods).
o
A lot of statistical theory goes back to
agricultural studies (e.g. “split-plot design” in ANOVA).
·
Computing
Science:
o
The newer machine learning methods often make
extensive use of statistical theory:
o
Computer network design makes use of principles
from probability theory for matter such as queuing algorithms.
·
Psychology
and Other Quantitative Social Sciences:
o
These disciplines make extensive use of statistical
methods, such as regression, ANOVA, factor analysis and cluster analysis.
o
Demography is an important sub-discipline of
sociology, which is very statistical in nature.
·
Economics:
o
Economics makes extensive use of various types
of regression analysis (e.g. OLS, logit, time series) and other very complex
methods.
o
Marketing is very heavily dependent on
statistical analysis. In fact, many
statistical methods came about for marketing purposes (e.g. A/B studies).
·
Medicine:
o
Makes very extensive use of statistical theory
to determine the efficacy of new drugs and treatments.
o
Meta-analysis is widely used to do “studies of
studies”.
o
Epidemiology is essentially statistical in
nature (e.g. the famous study of how typhus was spread via water pumps was
essentially a correlation study).
Here are a few more light-hearted examples of the use of statistics in science, mostly from XKCD:
Interpreting p-values for your research paper.
A bit of everyday sociology, using statistics.
o
Data Science overconfidence.
o
Earthquake prediction.
o
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Now that you have read about science and statistics, you might want to relax and read some science fiction. The Witch’s Stones series would be an excellent choice. Alternatively, you could try the short story “The Magnetic Anomaly”, a SF story which includes an example of the use of statistical methods in geophysics, namely Fourier Analysis (though there are no equations).
Now that you have read about science and statistics, you might want to relax and read some science fiction. The Witch’s Stones series would be an excellent choice. Alternatively, you could try the short story “The Magnetic Anomaly”, a SF story which includes an example of the use of statistical methods in geophysics, namely Fourier Analysis (though there are no equations).
The Witches’ Stones
Or, you might prefer, the trilogy of the Witches’ Stones
(they’re psychic aliens, not actual witches), which follows the interactions of
a future Earth confederation, an opposing galactic power, and the Witches of
Kordea. It features Sarah Mackenzie,
another feisty young Earth woman (they’re the most interesting type – the
novelist who wrote the books is pretty feisty, too).
The Magnetic Anomaly: A Science Fiction Story
“A geophysical crew went into the Canadian north. There were
some regrettable accidents among a few ex-military who had become geophysical
contractors after their service in the forces. A young man and young woman went
temporarily mad from the stress of seeing that. They imagined things, terrible
things. But both are known to have vivid imaginations; we have childhood
records to verify that. It was all very sad. That’s the official story.”
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