The CSV file is here: https://github.com/JuliaStats/GLM.jl/files/6384056/Car-Training.csv

The GLM issue that I reported is here: Incorrect linear regression results · Issue #426 · JuliaStats/GLM.jl · GitHub

The codes are very simple:

```
using GLM
using DataFrames
using CSV
data = CSV.read( "Car-Training.csv", DataFrame )
model = @formula( Price ~ Year + Mileage )
results = lm( model, data )
```

Could you see if I did something wrong here? It seems so basic but yet I got strange results that are wrong:

```
StatsModels.TableRegressionModel{LinearModel{GLM.LmResp{Array{Float64,1}},GLM.DensePredChol{Float64,LinearAlgebra.CholeskyPivoted{Float64,Array{Float64,2}}}},Array{Float64,2}}
Price ~ 1 + Year + Mileage
Coefficients:
─────────────────────────────────────────────────────────────────────────────────
Coef. Std. Error t Pr(>|t|) Lower 95% Upper 95%
─────────────────────────────────────────────────────────────────────────────────
(Intercept) 0.0 NaN NaN NaN NaN NaN
Year 8.17971 0.167978 48.70 <1e-73 7.84664 8.51278
Mileage -0.0580528 0.00949846 -6.11 <1e-7 -0.0768865 -0.0392191
─────────────────────────────────────────────────────────────────────────────────
```