# Analyzing regression results

I have done a regression model where i determine the number of cubes (independent variable) based on the amount of units i started with for each product type (dependent variables, X1, X2, X3, X4, X6, X9, X10, X15). But i would like a second opinion on the results, because the tests for heteroscedasticity i did (Breusch-Pagan and white test) suggests my data has heteroscedasticity. But i think it is because i have alot of data (500 000 observations). Looking at the graphs below i don't seem to pick up much heteroscedasticity, although there do seem to be outliers in my data. But i would like to have a second opinion and want to know does my results look fine so that i can use this regression model and can assume (1) my residuals close enough to a normal distribution and (2) there is little sign of heteroscedasticity?

Here is the coefficients

Coef Estimate Std. Error t value Pr(>|t|) X1 0.023493012 0.000497393 47.23233675 0 X2 0.002248871 0.000777214 2.893502743 0.003811022 X3 0.069934116 0.000484908 144.2215372 0 X4 0.084532734 0.000883563 95.67252408 0 X6 0.014607296 0.000458375 31.86759025 4.43E-221 X9 0.409846348 0.001738917 235.6905778 0 X10 0.128915999 0.000468583 275.1187379 0 X15 0.042864773 0.001276817 33.57157987 6.58E-245

R-squared: 0.8158 Adj R-squared: 0.8158 F-stat: 3.47e+04, p-value < 2.2e-16

Here is all the graphs.

• There's very clear indication of heteroskedasticity. There's also suggestion of lack of fit. – Glen_b -Reinstate Monica Jul 27 '14 at 1:45