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In general, you wouldn't necessarily expect one way ANOVA and the Kruskal-Wallis to be similar, sometimes they can give quite different p-values. See here for a little partial motivation for why you might expect a difference. [When samples are reasonably normal-looking and with means not too many standard errors apart, they often tend to give similar p-values. Outside that, they frequently don't.]

In general, you wouldn't necessarily expect one way ANOVA and the Kruskal-Wallis to be similar, sometimes they can give quite different p-values. See here for a little partial motivation for why you might expect a difference. [When samples are reasonably normal-looking and with means not too many standard errors apart, they often tend to give similar p-values. Outside that, they frequently don't.]

In general, you wouldn't necessarily expect one way ANOVA and the Kruskal-Wallis to be similar, sometimes they can give quite different p-values. See here for a little partial motivation for why you might expect a difference.

In general, you wouldn't necessarily expect one way ANOVA and the Kruskal-Wallis to be similar, sometimes they can give quite different p-values. See here for a little partial motivation for why you might expect a difference. [When samples are reasonably normal-looking and with means not too many standard errors apart, they often tend to give similar p-values. Outside that, they frequently don't.]

Your p-value for the Kruskal-Wallis is wrong.

In general, you wouldn't necessarily expect one way ANOVA and the Kruskal-Wallis to be similar, sometimes they can give quite different p-values. See here for a little partial motivation for why you might expect a difference.

However, in this case the reason is more prosaic: Your Kruskal-Wallis p-value is wrong.