Multiple linear regression model using R | lm( ) | variations of MLR | visualize results coefplot( )

In this video, you will learn to do data visualization on a complicated dataset with categorical and numerical variables. You will also learn to build a few variations of the multiple linear regression model. In the end, you will find the visualization of model results using coefplot package of the five MLR models.
0:00 intro of the topic and the data
1:43 import data and visualize it
4:35 histogram (distribution of price)
7:02 histogram using facet_wrap
8:40 scatter plot of price~mileage, MAKE colored
10:55 GGally: pairwise graphs of a set of variables
12:29 change the variables into the correct data types
15:12 use lm( ) to fit a multiple linear regression
16:45 model2: add one more variable and fit it
17:45 model 3: add interactions
19:55 model 4: scale one variable
21:50 model 5: change the unit of the response variable
22:50 visualize the model results

The models in this video are for illustration purposes only. They are not the best models.

The dataset I used in the video: https://github.com/yz-DataScience/R-f...
excel file is easier to be downloaded directly. Make sure you click file-import file- import from excel if you are using the car.xls file.
The car.csv file: https://github.com/yz-DataScience/R-f...
you may click copy raw contents, paste it to excel, and save it as car.csv

The r code with annotations: https://github.com/yz-DataScience/R-f...

Feel free to leave me comments of any quesitons.