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 件のコメント
Constantino Carlos Reyes-Aldasoro
2024 年 6 月 6 日
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:
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