How to obtain Residual Variance in a linear regression

[KimFong]

Dear fellows,
I am a self-learner in e-views, I am analysis the CAPM model.
here is the model,
rpt = αp + βp ∙ rmt + εpt,
My question is how I can get the Residual Variance, σ2 (εpt) from E-views.
I have done the linear analysis, and is it the value of Sum Squared Resid that appears in the E-views output
equal to the Residual Variance?
If it is not, how should I run on E-views to get the Residual Variance.
Thank You. I really appreciate your help.

Regards,
Frank

[startz]

The standard error of the regression (marked "S.E. of regression") is an estimate of the square root of the residual variance.

[KimFong]

Thanks Startz,
I'm very appreciate your answer.

Now, I'm facing another test problem, which is Wald Test on the hypotheses.
rp = γ0 + γ1 ∙ βp + γ2 ∙ βp2 + γ3 ∙ RVp + εp
where,
γ0 = 0, test the intercept of Security Market Line in CAPM,
γ1 > 0 that is, there is a positive price of risk in the capital markets,
γ2 =0 or there are no nonlinearities in the security market line,
γ3 =0 or residual risk does not affect return.
What should i specify in the specification box, is it like below?
c(1)=0, c(2)=1, c(3)=0, c(4)=0
And how to interpreting the output?
Is it p-value less than 0.05, reject the null hypothesis, which is the value I restricted in the specification box? (95% level of study)
How to interpret the F-statistics and degree of freedom as well.

I really need someone to guide me in E-views analysis...
Thank you