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amoeba
amoeba
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Does larger How can MANOVA report a non-significant p-value for MANOVA necessarily means it is harder to find a "discriminant axe" to classify data? Any expectionswhile LDA results in perfect separation of two groups?

I am new to statistics and currently got a dataset which contains 80$80$ dependent variables and 1$1$ independent variable with 2$2$ groups. MANOVA hasreports a p$p$-value of >0.6$> 0.6$ on this dataset. But when I use linear discriminant analysis (LDA), two groups can be separated perfectly  (almost 100%$100\%$). 

Is this result possible?

What I understand for MANOVA is that larger p$p$-value means less differentdifference between two groups. Then how can datathe groups be separated perfectly if there is no differentdifference between them?

Does larger p-value for MANOVA necessarily means it is harder to find a "discriminant axe" to classify data? Any expections?

I am new to statistics and currently got a dataset which contains 80 dependent variables and 1 independent variable with 2 groups. MANOVA has a p-value of >0.6 on this dataset. But when I use linear discriminant analysis, two groups can be separated perfectly(almost 100%). Is this result possible?

What I understand for MANOVA is that larger p-value means less different between two groups. Then how can data be separated perfectly if there is no different?

How can MANOVA report a non-significant p-value while LDA results in perfect separation of two groups?

I am new to statistics and currently got a dataset which contains $80$ dependent variables and $1$ independent variable with $2$ groups. MANOVA reports a $p$-value of $> 0.6$ on this dataset. But when I use linear discriminant analysis (LDA), two groups can be separated perfectly  (almost $100\%$). 

Is this result possible?

What I understand for MANOVA is that larger $p$-value means less difference between two groups. Then how can the groups be separated perfectly if there is no difference between them?

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Adrian
Adrian
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Does larger p-value for MANOVA necessarily means it is harder to find a "discriminant axe" to classify data? Any expections?

I am new to statistics and currently got a dataset which contains 80 dependent variables and 1 independent variable with 2 groups. MANOVA has a p-value of >0.6 on this dataset. But when I use linear discriminant analysis, two groups can be separated perfectly(almost 100%). Is this result possible?

What I understand for MANOVA is that larger p-value means less different between two groups. Then how can data be separated perfectly if there is no different?