Methodology of Scientific Research
also known as MSR
also known as MıSıR
also known as 🌽
Who
Why
How
What
Answer now with your voice
In this course we will speak about
Good practices doing science
We will learn to observe, communicate and collaborate better
We want to help you to become
Lower failure rate in your experiments
Do better experiments
Ask better questions
Achieve larger impact
Ask better questions
Propose better answers
Create Knowledge, not only Data
Perhaps you will change your career later in life
Whatever you do, do your best work
Always follow good practices
Perhaps you will win the lottery
(or inherit many million dollars from a distant uncle)
and you do not work anymore
Still, you need to understand the world
Enough so big companies cannot fool you
We need to see the Big Picture,
How did we get to here and now?
(second part of the course)
One of the essential good-practices of laboratory work is the Lab Notebook
They are essential if you want to get a patent for something you create
They are essential to carry long term experiments
We encourage you to use a good quality notebook every day
Do not trust your memory
Our homepage is at https://www.dry-lab.org/blog/2024/msr/
It is part of my blog https://www.dry-lab.org/
Homework and class slides are published there
I also have a YouTube channel https://www.youtube.com/@dr.andresaravena
Scientist work is to understand Nature
We start by Observing Nature, usually measuring values
These are exploratory experiments
This is the first part of our course
The thing we study must be reproducible, and we need to see that repetition
We can find them using plots, linear models, clustering, etc.
This is the most important part
Good answers to bad questions are useless
Good questions are good, even if we don’t have answers
We answer these questions using models and explanations
Valid models should make predictions that we can test in the lab…
These are validation experiments.
If the results do not match the prediction, we know that the explanation is wrong. Two steps back.
Now we publish our data and model, so other scientists validate or reject it.
The final validation is to be published.
If the paper is accepted and published, our work becomes part of our shared human knowledge.
The goal of Science is to produce new Knowledge.
When we observe Nature we use our previous Knowledge
We look for new Patterns that raise new Questions.
“Noise becomes Signal”
(some people say)
Daniel Kahneman, 2002 Nobel Memorial Prize in Economic Sciences
Fast
Slow
So System 1 is the default mode
Most of the time we use the cheap intuitive system
Rational thinking (i.e. math) is not spontaneous
One option is to be like Spock, and suppress all intuition
The other option is to train our intuition
This is why we have been practicing estimating magnitudes
Not let our intuition fool us
Get a gut feeling about numbers
This last part is important, because we make decisions based on our feelings, and often we do not know what to feel about a number
At first, we estimate by powers of 10
(after choosing the appropriate units)
We even have names for some of them them:
deci, centi, milli, micro, nano, pico
deca, hecto, kilo, mega, giga, tera, peta, exa
In powers of ten, how many people live in Turkey?
Be brave, take a guess
(no books, no Google, no ChatGPT, no Internet, only guess)
When estimating a value, we usually can guess that the real value is somewhere between two values
In other words, we guess lower and upper bounds \(L\) and \(U\)
Choose the smallest value that seems right,
then the largest one
Remember: we are looking for two numbers
The order of magnitude of a value is its power of 10
More precisely, is the integer part of the logarithm base 10
We say that two quantities are in the same order of magnitude if their ratio is between 0.1 and 10
i.e. if each one is less than ten times the other
Which of these populations are of the same order of magnitude?
Instead of going \[10^{-1}, 10^{0}, 10^{1}, 10^{2}, 10^{3}\] we can increment the exponent by 0.5 \[10^{-1}, 10^{-0.5}, 10^{0}, 10^{0.5}, 10^{1}\]
Since \(10^{0.5} = \sqrt{10}≈ 3.16≈3\) we can say \[0.1, 0.3, 1, 3, 10, 30, 100,…\]
Our campus has a park, near Astronomy department
How many trees are there?
The speed of light is about 300000000 m/s
It is easy to miscount the number of “0”
Instead, we write 3×108 m/s$
Better, in computers we write 3E8
(This is called exponential notation)
Here 3
is called mantissa and 8
is
the exponent
In USA, a billion is a thousand millions
In the rest of the world, a billion is a million millions
(often called “a milliard”)
There are two conventions: short scale and long scale
To avoid confusion, better use giga or tera
or use scientific notation: 109, 1012
Please read The Library of Babel by J.L.Borges