Linear Regression Model
parsnip model object
Call:
stats::lm(formula = cost_diff ~ Gas_cost + Cost_per_kWh, data = data)
Coefficients:
(Intercept) Gas_cost Cost_per_kWh
4.075e-12 1.620e+03 -1.215e+04
# A tibble: 3 × 7
term estimate std.error statistic p.value conf.low conf.high
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) 4.08e-12 1.13e-12 3.59e 0 0.000767 1.80e-12 6.36e-12
2 Gas_cost 1.62e+ 3 2.85e-13 5.69e15 0 1.62e+ 3 1.62e+ 3
3 Cost_per_kWh -1.21e+ 4 2.11e-12 -5.75e15 0 -1.22e+ 4 -1.21e+ 4
LaTeX Code
\[
\begin{equation}
\text{Cost Difference}_i = \beta_0 + \beta_1 \times \text{Gas Cost}_i + \beta_2 \times \text{Cost per kWh}_i + \epsilon_i
\end{equation}
\]
Where:
\(\beta_0\): This represents the cost difference when both gas and charging prices are zero.
\(\beta_1\): This represents how much the cost difference changes for regular gas price.
\(\beta_2\): This represents how much the cost difference changes for charging costs per kWh.