best_lm_model: Best Linear Model
In stuckinthe16th/best.model: Best Statistical Model

This function helps you select the best linear model given your dataset. Allows you to define a denpendent variable, any variables you wish to have in your final model and which type of optomized liner model you would like returned. Provides both Adjusted R^2 and p-value optimized models.

1 2	best_lm_model(data, dep_var = "", keep_vars = list(), ignore_vars = list(), return = "all")

`data`	A `data.frame()` object which contains the data you wish to model.
`dep_var`	A `string` containing the dependent variable you wish your model to measure. Defaults to the first column of `data`.
`keep_vars`	A `string`, or `list()` of `strings`, which represents the variables you want to keep in your final model regardless of their effects on the final model's optimization.
`ignore_vars`	A `string`, or `list()` of `strings`, which represents the variables you want to exclude in your final model regardless of their effects on the final model's optimization.
`return`	A `string` object that represents the type of model you would like to return. "base" returns a linear model of all of the variables through the obect `model_base` and a summary table of that model. "r2" returns an Adjusted R^2 optimized linear model of the data through the obect `model_r2` and a summary table of that model. "p" returns a p-value optimized (95% signifigance) linear model of the data through the obect `model_p` and a summary table of that model. "all" returns all of the above `model` objects and summary tables. `return` defaults to "all".