Assumptions of linear regression

Among the four basic assumptions, can anyone explain what does it mean by:

the expected value of error/residual will be zero and there will be constant variation on error/residual term

This means that the regression is an unbiased estimator of the dependent variable: if the regression gives you a value of, say, 1.6, then the expected value of the dependent varaible is 1.6.

This means that, for example, the errors don’t get bigger as x gets bigger and smaller as x gets smaller. The technical name for this is homoskedasticity <hoe-mow-skee-dass-tiss-it-tee>; it’s the opposite of h_eteroskedasticity_ , and it means that the standard errors will be accurate.

Thanks alot.

do put it on financialexamhelp123

I’m doing a ton of work on instructor slides for Wiley at the moment, so I won’t be getting back to the website till the end of January or so.

But it’s on the list.