Here is some advice for bachelor and masterstudents that write a thesis at the department of Biophysics at the Donders Institute for Brain, Cognition and Behaviour.
English is the scientific language, so it is essential that you learn to write in english.
Section  Purpose 

Abstract/Summary  summarizing experiment, results, conclusions 
Introduction  establish the topic, explain what has been done inf the field, clarify what interesting question remains, and how you will tackle this 
Methods  A description of the subjects, experimental setup, paradigms and data analysis 
Results  A presentation of the results and analysis (both in words and graphics) 
Discussion  reporting main conclusions, comparison with other studies, putting your results in a bigger picture, (perhaps suggesting a model) 
On your frontpage, put:
The paragraphs in your Introduction should contain the following:
The Methodssections is usually straightforward, containing the following subsections:
If you want to use the classical nullhypothesis significance testing, then here are some reporting guidelines from the journals of the American Physiological Society:
Table 1. Interpretation of P values
P Value  Interpretation 

\( P \nsim 0.1 \)  Data are consistent with a true zero effect 
\(0.05 \sim P \simeq 0.05 \)  Data suggest there may be a true effect that differs from zero 
\( 0.01 \nsim P \simeq 0.05 \)  Data provide good evidence that the true effect differs from zero 
\( P \simeq 0.01 \)  Data provide strong evidence that the true effect differs from zero 
Table 2.Guidelines for rounding P values to sufficient precision
P value range  Rounding Precision 

\( 0.01 \leq P \leq 1.00 \)  Round to 2 decimal places: round P=0.031 to P=0.03 
\( 0.001 \leq P \leq 0.009 \)  Round to 3 decimal places: round P=0.0066 to P=0.007 
\( P \lt 0.001 \)  Report as P<0.001; more precision is unnecessary 
It is much better to use Bayesian statistics. With current Markov Chain Monte Carlo sampling techniques it is easy to do Bayesian statistical analysis. For a course on Bayesian statistics, see "Bayesian Cognitive Modeling: A Practical Course" (which contains a free downloadable book). A very good book on Bayesian statistics is from John Krushke: Doing Bayesian Data analysis with R.
Bayesian null hypothesis testing is often done with the Bayes factor, which has the following interpretation.
Table 3. Interpretation of Bayes factor (Jeffreys 1961, Bayesian Cognitive Modeling: A Practical Course)
Bayes factor BF12  Interpretation 

\( \gt 100 \)  extreme evidence for model 1 
\(30 \leq BF \leq 100 \)  very strong evidence for model 1 
\( 10 \leq BF \leq 30\)  strong evidence for model 1 
\( 3 \leq BF \leq 10 \)  moderate evidence for model 1 
\( 1 \leq BF \leq 3 \)  anecdotal evidence for model 1 
1  no evidence 
\( 1/3 \leq BF \leq 1 \)  anecdotal evidence for model 2 
\( 1/10 \leq BF \leq 1/3 \)  moderate evidence for model 2 
\( 1/30 \leq BF \leq 1/10 \)  strong evidence for model 2 
\( 1/100 \leq BF \leq 1/30 \)  very strong evidence for model 2 
\( \lt 1/100 \)  extreme evidence for model 2 
In the resultssection you have to guide the reader along, explaining what results you have found and what kind of analyses you did. You should start with the basic data, and gradually increase the level of analysis.
So, usually the first figure in the resultssection contains the raw data of one typical subject (such as a head movement trace, or a stimulusresponse plot). With this figure you can introduce a more elaborate analysis, such as linear regression. Next you have to make the results quantitatively, so you want to have a measure for all subjects/conditions that you can easily plot in for example a histogram. This "first typical example""then quantification" abounds in scientific articles.
Don't: "Regression analysis was done, and the results of listener JB are plotted in figure X. "
Do: "listener JB accurately localizes the sounds, as evidenced by a high stimulusresponse gain (gain = 0.9, see Methods, Figure X)".
The storyline is important. Each paragraph is preceded and followed by another paragraph. Link them together (use: therefore, however, next), and conclude.
A very important aspect of scientific reporting of data is data visualization. In your Matlabscript, you should usually see these commands:
Your figures should be saved as vectorformat epsfiles:
print('depsc','painter',mfilename)
There is almost never a reason to save a figure in bitmapformat. The epsfiles can be easily modified in Adobe Illustrator to make the figures more attractive (without distorting the data). And if you want to use Microsoft, Illustrator has an option to save your figure for Officepurposes.
Also very important: label your axes!
Also, you should use a readable font size (minimally 10 at the final stage).
Furthermore, remove as much "dead white space" as possible. For example, often you can plot several similar graphs in one figure, you can leave out the ticklabels for several of these graphs by correctly positioning them.
One of the hardest part in any thesis to write is the Discussion. In the Discussionsection you have to put your results in perspective.
Students have the tendency to embellish, exaggarate and reiterate (especially in the Introductionsection). Try to write in a concisive manner. Try to get your main point across quickly/immediately. Explain everyting what you need to explain, and nothing more. Shorten long sentences. Check your text for sentences like:
These sentence parts are superfluous, and can be easily removed (which often makes the text easier to read).
Don't overuse the verb "to be". Replace it with action verbs.
It is always a good idea to check and recheck your text. Your supervisors will also heavily edit your manuscript drafts. Don't be disappointed when your first draft is returned completely covered in red changes. Expect this to happen!
It is impossible to write your thesis in one day.
Write formally, so avoid:
I have heard from many students they have been taught also to avoid 'we' and that you should write in a passive form. Rubbish! The personal pronoun 'we' and writing in the active form is quite common in scientific papers. The active form actually speeds up reading. So, 'the listener localized sounds accurately' is better than 'the sounds were localized accurately by the listener'.
The most important rule is:
Don't write something absurd.
All other rules can be broken.
Also, because you can never be 100% certain of your conclusions, you should express yourself cautiously, using expressions such as:
Note that caution should also be used when discussing other people's results and conclusions (for example in introductions or reviews). Even though a statement is written down in stone (in Dutch "staat iets zwart op wit", in black and white), this does not make it true.
With a research article, you should convince your readers that your experiments are wellperformed and interesting. You should lead the readers along, convince them of the mysteries or problems you want to tackle, and conclude with a solution. The goal is to report your findings and conclusions clearly and to the point. Think of an outline with a logical flow. Each paragraph should contain a clear topic. Importantly, you should communicate a storyline, having a specific purpose in mind for every section and paragraph. Describe, compare and argue.
To achieve cohesion of a text, connect sentences and paragraphs. Here are some examples of connectives.
type  Purpose  Examples 

and 


or 


but 


'Like' implies a comparison, 'such as' implies inclusion.