julia> dat = DataFrame(year = parse.(Int, df.Year), dist = df.nsmiles, fare = df.fare);

julia> dat.fuel = zeros(nrow(dat));

julia> dollars_per_mile = 55e3/3500
15.714285714285714

julia> for i in 1:nrow(dat)
           yr_adj   = dat.year[i] - 1997
           cost     = yr_adj + dollars_per_mile
           dat.fuel[i] = cost*rand(Normal(dat.dist[i], .1*dat.dist[i]))
       end

julia> Base.show(io::IO, f::Float64) = @printf(io, "%.3f", f)

julia> dat
598712×4 DataFrame
    Row │ year   dist   fare     fuel
        │ Int64  Int64  Float64  Float64
────────┼──────────────────────────────────
      1 │  2004   1197  242.510  28402.239
      2 │  2003    758  136.000  18100.173
      3 │  2004   1259  193.880  30453.926
      4 │  2004    459  199.570  10225.836
      5 │  2003   1539  272.830  33089.690
      6 │  2009   1204  151.460  37194.516
      7 │  2008    625  165.170  14288.107
      8 │  2004    177  308.140   3585.322
      9 │  2003   1344  237.310  32611.485
     10 │  2013   1092  222.880  38626.476
     11 │  2009    725  144.110  17507.425
     12 │  2004    908  240.830  21925.639
     13 │  1996    120  217.470   1801.010
     14 │  1999    451  184.320   8088.234
     15 │  2000    692  172.830  13057.867
   ⋮    │   ⋮      ⋮       ⋮         ⋮
 598699 │  2023    554  339.980  21355.241
 598700 │  2023   1952  641.480  83612.077
 598701 │  2023    906  386.780  36761.092
 598702 │  2023    292  359.470  11487.393
 598703 │  2023    389  373.810  19620.612
 598704 │  2023   1965  484.690  72349.014
 598705 │  2023    607  321.970  26150.935
 598706 │  2023   1552  462.450  58225.166
 598707 │  2023    666  384.290  28960.803
 598708 │  2023    300  351.060  11784.692
 598709 │  2023    511   86.070  19933.461
 598710 │  2023    586  328.160  24534.626
 598711 │  2023    656  341.790  28920.411
 598712 │  2023    689  325.490  33122.007
                        598683 rows omitted

julia> lm(@formula(fare ~ dist), dat)

fare ~ 1 + dist

Coefficients:
─────────────────────────────────────────────────────────────────────────
               Coef.  Std. Error        t  Pr(>|t|)  Lower 95%  Upper 95%
─────────────────────────────────────────────────────────────────────────
(Intercept)  178.125       0.171  1040.06    <1e-99    177.789    178.461
dist           0.054       0.000   378.24    <1e-99      0.054      0.054
─────────────────────────────────────────────────────────────────────────

julia> lm(@formula(fare ~ dist + fuel), dat)

fare ~ 1 + dist + fuel

Coefficients:
─────────────────────────────────────────────────────────────────────────
               Coef.  Std. Error        t  Pr(>|t|)  Lower 95%  Upper 95%
─────────────────────────────────────────────────────────────────────────
(Intercept)  179.089       0.162  1106.33    <1e-99    178.771    179.406
dist          -0.007       0.000   -25.02    <1e-99     -0.007     -0.006
fuel           0.002       0.000   267.93    <1e-99      0.002      0.002
─────────────────────────────────────────────────────────────────────────