Congratulations! You have fitted a linear model. The ANOVA table for your model is
anova(params$x) noterms <- dim(anova(params$x))[1] - 1 pvalues <- anova(params$x)[1:noterms, 5]
r if(noterms == 1 & sum(pvalues < 0.05) > 0) {"Your model has 1 term and it is significant. That is really good! Have you checked your assumptions?"}
r if(noterms > 1 & sum(pvalues < 0.05) > 0) {paste("Your model has", noterms, "terms and some of them are significant. That is really good! Have you checked your assumptions?")}
r if(noterms == 1 & sum(pvalues < 0.05) == 0) {"Your model has 1 term but it is not significant. I am really sorry, but don't forget that p-values are a function of sample size, so maybe you can try with more replications or a larger sample size next time."}
r if(noterms > 1 & sum(pvalues < 0.05) == 0) {paste("Your model has", noterms, "terms but none of them are significant. I am really sorry, but don't forget that p-values are a function of sample size, so maybe you can try with more replications or a larger sample size next time.")}
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