Analyzing data sets that are not statistically significant

I have the attached data. Those are the testing results of fibre reinforced cement mortars. First column indicates lengths of fibre used and the second column indicates the volume ratios. Third coloumn I have porosity data. I analysed all the data statistically, but no combination found statistically significant (Based on P-vale, correlation coefficient and R-squared). Sometimes may be due to only three data points for each combination (For an instance at 6 mm length, how volume ratios affect porosity have three data points and etc.)So I would kindly would like to know wehther nay other machine learning or techniques are available to interpret these data interestingly and effectively to the scintific community? Becuase, as this, I have 4 more test paramters (not only porosity) and four fibre types as well.

THnak you in advance.

[Constantino Carlos Reyes-Aldasoro]

Doing statistical tests on populations with 3 values is not a very sensible approach, mathematically you can obtain these metrics, but you should have more points to make these really representative. The same will happen with Machine Learning.

Can you obtain more samples? That would be the best and then repeat your t-tests or whatever you are using.

Alternatively, better to display your measurements and try to interpret than to summarise with a metric that may not be representative.

[Mathieu NOE]

yeap

too few samples

I was thinking fitting a plane or a higher order surface , but the porosity data seems more or less randomly distributed

T = readtable("Book4.xlsx");

Warning: Column headers from the file were modified to make them valid MATLAB identifiers before creating variable names for the table. The original column headers are saved in the VariableDescriptions property.
Set 'VariableNamingRule' to 'preserve' to use the original column headers as table variable names.

Length = T.Length;
VolumeRatio = T.VolumeRatio;
Porosity = T.Porosity;

scatter3(Length,VolumeRatio,Porosity,'filled');

[Pramodya]

Thank you so much for your answer. Yah I also feel the same after discussing with you all.

[Pramodya]

Thank you so much @ Constantino Carlos Reyes-Aldasoro yah from your explanation also I understood that just interpretting using some scatter plots or similar rather would be better. thank you again.

[Constantino Carlos Reyes-Aldasoro]

Happy to help. For the longer term, I can highly recommend the book "The Art of Statistics" by David Spiegelhalter. It is very nicely written, well explained and not full of mathematics so it is easier to understand than a normal textbook in Stats:

https://www.penguin.co.uk/books/294857/the-art-of-statistics-by-spiegelhalter-david/

[Pramodya]

Thank you so much for the recommendation, @Constantino Carlos Reyes-Aldasoro. I took a glimpse following your recommendation and found it to be rather simple and easy to understand, as you mentioned. Thank you very much. I will go through the book in detail.