1. Create a new ipynb file in your Jupiter note

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1.1. Create a new ipynb file in your Jupiter note
2. Add codes to load the data(attached) into your project.
3. Split dataset into training and test dataset, use training dataset to create the model.
4. Carefully evaluate whether you can use a linear regression model for your data set and clean or transform your data set. (e.g. ScatterPlot, BoxPlot, Histogram/DensityPlot)
5. Implement multiple linear regression against your dataset.
-Figure out the useful independent variables (continuous/categorical) to your dataset and select which variables you would like to use
-Find out the interactions of variables (between continuous/categorical)
-May need to go back and forth
6. Run the diagnostic test on the model you created, predict the test dataset and get the performance.
7. Interpret the result and how you want to use your model.
8. Prepare a powerpoint with slides.
-Should include the purpose of your analysis
-How your dataset looks like and the possible transformation
-The general steps of finding a multiple linear regression model
-Interpretation of the model and how you want to use it
-Possible further steps in the furture.
Data pulled from:
Car Price Prediction Multiple Linear Regression

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