Case Study: Predicting Car Sales Based on Advertising Spend

Background

A car dealership wants to understand how their advertising spend influences car sales. The goal is to use past data to build a predictive model that estimates future sales based on advertising expenses.

Data Collection

The dealership collected monthly data over the past 12 months, which includes the amount spent on advertising (in thousands of dollars) and the number of cars sold

1. Fit a Linear Regression Model
2. Introduction
3. Body
4. Implication
5. Conclusion
6. references

5.Provide some actionable insights

Month	Advertising Spend (X)	Cars Sold (Y)
Jan	23	63
Feb	25	70
Mar	20	77
Apr	30	78
May	35	67
Jun	40	80
Jul	45	89
Aug	38	90
Sep	33	75
Oct	50	90
Nov	27	68