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general:scientificworking [2021/10/13 21:17] – [Hypothesis testing] ingogeneral:scientificworking [2022/11/17 14:13] (current) – [Keep your workspace clean] vinh
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 ==== Hypothesis testing ==== ==== Hypothesis testing ====
-As a rule of thumb, hypotheses are only then scientific hypotheses if they are falsifiable. In essence, you need to be able to make an observation that cannot be explained by the hypothesis. :?: What does it now mean when your attempts failed to falsify/reject your hypothesis? Well, to be honest, not much. This is because you then always have a flank open to the critique that you did not try hard enough((in statistical terms, the power of your test was not sufficient)). As a take home message, :!: it is very  hard to support a hypothesis, and you are always better off to think of a hypothesis as something that is most likely wrong, but thus far explains the data best. In scientific practice, we often face the problem to decide between two competing hypotheses. Typically, we then assign one --probably the simpler, probably older and better accepted hypothesis-- the term //NULL hypothesis// (H<subt>0</sub>), whereas the newer, competing hypothesis is called the alternative hypothesis (H<sub>A</sub>). Statistical tests, such as likelihood ratio tests if the two hypotheses are nested, or Akaike Information Criterion (AIC) or Bayesian Information Criterion (BIC) together with their derivates if they are not, help then to decide whether H<sub>A</sub> explains the data :!: significantly better than H<sub>0</sub>. Only then H<sub>0</sub> is considered rejected. But remember, <wrap important></wrap>this does by no means indicate that H<sub>A</sub> is true!   +As a rule of thumb, hypotheses are only then scientific hypotheses if they are falsifiable. In essence, you need to be able to make an observation that cannot be explained by the hypothesis. :?: What does it now mean when your attempts failed to falsify/reject your hypothesis? Well, to be honest, not much. This is because you then always have a flank open to the critique that you did not try hard enough((in statistical terms, the power of your test was not sufficient)). As a take home message, :!: it is very  hard to support a hypothesis, and you are always better off to think of a hypothesis as something that is most likely wrong, but thus far explains the data best. In scientific practice, we often face the problem to decide between two competing hypotheses. Typically, we then assign one --probably the simpler, probably older and better accepted hypothesis-- the term //NULL hypothesis// (H<sub>0</sub>), whereas the newer, competing hypothesis is called the alternative hypothesis (H<sub>A</sub>). Statistical tests, such as likelihood ratio tests if the two hypotheses are nested, or Akaike Information Criterion (AIC) or Bayesian Information Criterion (BIC) together with their derivates if they are not, help then to decide whether H<sub>A</sub> explains the data :!: significantly better than H<sub>0</sub>. Only then H<sub>0</sub> is considered rejected. But remember, <wrap important></wrap>this does by no means indicate that H<sub>A</sub> is true!   
  
 ===== Scientific reasoning ===== ===== Scientific reasoning =====
-Science is arguing, because nobody knows the truth. +Let's start with a simple statement: Science is arguing, because nobody knows the truth. Arguing requires...right... **Arguments**. But what are these arguments? In the first approximation, they are statements that are backed up by :!: either experimental data, or :!: a reference to a study where somebody else collected the data in support of the statement. It might be easy to think of scientific reasoning as a building that you create. A solid foundation is essential, but a house of cards built on concrete foundations will also easily collapse, if you get the line. To cut a long story short, your reasoning is exactly as solid and stable as it is the weakest supported statement that you recruit. So, stay away from //hearsay//, //anecdotal evidences//, or //handwaving argumentation//.      
  
- +===== Scientific documentation should be FAIR ===== 
-we would like to mention a couple of aspects that may make your life easier as the course proceeds. First and foremost, this is a **scientific project**, and we expect you to [[general:dokuwiki:how2document|document your work]] very carefully. The requirements are easily specified: :!: You need to document to an extent that any third person is capable of understanding **why** you have done **what** and **how**, what the **results** are, and to what extent your **conclusions are supported by the data**. It may happen over time that you are a bit lost by the amount and thematic breadth of our analyses. No worries, this happens to all of us sometimes, just make sure to ask, discuss and read in time.+Scientific projects have to be [[general:dokuwiki:how2document|documented]] very carefully. The requirements are easily specified: :!: You need to document to an extent that any third person is capable of understanding :!: why you have done :!: what and :!: how, what the :!: results are. You also have to make clear to what extent your :!: conclusions are supported by the data. When it comes to your data, make sure to follow the [[https://www.go-fair.org/fair-principles/|FAIR principles]]. This means that your data has to be 
 +  - **F**indable 
 +  - **A**ccessible 
 +  - **I**nteroperable 
 +  - **R**eproducable 
 +In particular, if the **F** and the **R** of the [[https://www.go-fair.org/fair-principles/|FAIR principles]] are not met, then your project is scientifically no more worth than story telling.
 ==== Keep your workspace clean ==== ==== Keep your workspace clean ====
  
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   * **Avoid the use of whitespaces**  and language specific characters such as ”ä”, ”ö”, ”ü” in both file and folder names, as this can cause problems when working with the linux terminal.   * **Avoid the use of whitespaces**  and language specific characters such as ”ä”, ”ö”, ”ü” in both file and folder names, as this can cause problems when working with the linux terminal.
   * Keep input data separate from results, as you may do different analyses with the same input data. If you insist in having the input together with the results, consider the use of soft links. These are pointers to a file or a directory that can be placed anywhere in the file system without the need to duplicate the often large input files.   * Keep input data separate from results, as you may do different analyses with the same input data. If you insist in having the input together with the results, consider the use of soft links. These are pointers to a file or a directory that can be placed anywhere in the file system without the need to duplicate the often large input files.
 +
 +<WRAP tabs>
 +   * [[ecoevo_molevol:course_introduction|Back to EcoEvo course]]
 +   * [[pbioc_basics:start|Back to PBioC course]]
 +   * [[digikomp_bio:course_introduction|Back to DigiKomp course]]
 +</WRAP>