**indicate the working path
cd "C:\Users\Aki\Documents\stata"
log using april4.log, replace

****APRIL 4. LINEAR REGRESSION******
use nlsw, clear

**checking for outliers
graph box wage, over(country)
sort wage country

**checking for distribution
hist wage, by(country)

**checking the variances for the homoscedasticity comes after running the OLS regression


**OLS REGRESSION******
**dependent variable is continous
**assumptions for OLS (Gauss-Markov assumptions) to have OLS as BLUE
**reg dependentvar independentvar1 independentvar2 
help regress

**what are the determinants of car price?
sysuse auto, clear

reg price mpg weight length

**what if there are dummy/categorical variables in regression?

reg price mpg weight length i.rep78 i.foreign
//foreign cars on average are 3277.5 dollars more expensive than domestic cars

**OLS REGRESSION DIAGNOSTICS
**goodness of fit, outliers, heteroskedasticity, function form problems

*linear prediction from the model into the variable xb
predict priceb, xb
predict residual, residuals
summarize priceb residual

sum price

**in OLS, error term is normally distributed
kdensity residual
//not normally distributed

gen lprice = log(price)
reg lprice mpg weight length i.rep78 i.foreign

predict lpriceb, xb
rename residual residual1
predict residual, residuals
kdensity residual

rvfplot
//this is a scatterplot of the residuals against the predicted values
//you want the residuals to be randomly distributed (no clear pattern)
log close