I have a multiple regression model relating salary, with 3 predictors.

I am given the ANOVA table of this model. It looks like this enter image description here

I have completed the NAs and now want to test at the 10% significance level whether or not the linear regression model explains significantly more variability in Salary than a model with no explanatory variables. Is the null hypothesis $H_0$: $β_1$ = $β_2$ = $β_3$ = 0? This is also related with $r^2$, how can I perform the hypothesis testing? Also, what assumptions shall we make?

I really appreciate your help!


You can compare two models using ANOVA by fitting them separately as linear models (say lm1 and lm2), then calling anova(lm1,lm2,test="Chisq") in the R language. It will test if the reduction in sum-of-squared residuals is significant.

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