Analyzing data sets that are not statistically significant
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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.
6 个评论
Constantino Carlos Reyes-Aldasoro
2024-6-6
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.
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");
Length = T.Length;
VolumeRatio = T.VolumeRatio;
Porosity = T.Porosity;
scatter3(Length,VolumeRatio,Porosity,'filled');
Pramodya
2024-6-6
Pramodya
2024-6-6
Constantino Carlos Reyes-Aldasoro
2024-6-6
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:
Pramodya
2024-6-7
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