Comprehension of correlation coefficiant |r| (what is the cut-off)

FrancesBudgie97 — Fri, 18 Sep 2026 08:47:10 GMT

Hello all,

I am currently working on a L9 Taguchi matrix design of experiments. I have three parameters that have three levels each and I observe their effects on continuous outputs like pH. I want to see how the pH evolves depending on my three inital factors.

By construction, the L9 matrix considers only principal effects and neglects the interaction between terms. More specifically, it aliases two-factor interractions with main effects. This allows us to limit the number of experiments. In this case, only 9 experiments are necessary.

Since I am doing this work for my PhD, I wish to also justify leaving interraction terms behind by giving the correlation between terms (in Evaluate window). How do I understand the limit of what to consider correlated? I have values of |r| going up to 0,58. In my old statistics classes, I remember the cutoff being at |r| = 0,7 or 0,8 typically.

How can I justify not using two-factor interractions in my final model ?

Thanks for your help!

Anna

Re: Comprehension of correlation coefficiant |r| (what is the cut-off)

FrancesBudgie97 — Fri, 18 Sep 2026 09:10:15 GMT

Feel free to ask for any extra details !

Re: Comprehension of correlation coefficiant |r| (what is the cut-off)

statman — Fri, 18 Sep 2026 14:20:32 GMT

I would graph the relationships with scatter plots and consider the practical significance of the relationships rather than relying specifically on a statistic which may be influenced by unusual data points.

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Comprehension of correlation coefficiant |r| (what is the cut-off)

Re: Comprehension of correlation coefficiant |r| (what is the cut-off)

Re: Comprehension of correlation coefficiant |r| (what is the cut-off)