Define a code template tpl:
tpl = 'lm(mpg ~ %s, data = mtcars) |> summary() |> coef()'
x_vars = names(mtcars)[2:4]
We run regressions on three variables one by one:
lm(mpg ~ cyl, data = mtcars) |> summary() |> coef()
|
Estimate |
Std. Error |
t value |
Pr(>|t|) |
| (Intercept) |
37.885 |
2.074 |
18.268 |
0.000 |
| cyl |
-2.876 |
0.322 |
-8.920 |
0.000 |
lm(mpg ~ disp, data = mtcars) |> summary() |> coef()
|
Estimate |
Std. Error |
t value |
Pr(>|t|) |
| (Intercept) |
29.600 |
1.230 |
24.070 |
0.000 |
| disp |
-0.041 |
0.005 |
-8.747 |
0.000 |
lm(mpg ~ hp, data = mtcars) |> summary() |> coef()
|
Estimate |
Std. Error |
t value |
Pr(>|t|) |
| (Intercept) |
30.099 |
1.634 |
18.421 |
0.000 |
| hp |
-0.068 |
0.010 |
-6.742 |
0.000 |