Data Science Classroom Series – 28/Nov/2021

Practical Regression Problem

  • Lets try to do the regression analysis of the the following dataset Refer Here

  • Lets check for Linearity

    • Mileage vs price Preview
    • Engine vs price Preview
    • Year vs price Preview
    • Mileage vs log(price) Preview
    • Engine vs log(price) Preview
    • Year vs log(price) Preview
  • Since we have 7-distinct categories in category variable Brand, we have created the six dummy variables (Rule => n-1) Preview

  • Lets create one more variable for log(mileage) just for understanding Preview

  • Regression Analysis of

    • Log price and Log mileage Preview
    • Log price and year Preview
    • Log price and Engine Preview
    • log price and log mileage, year and Engine Preview
    • Log price vs log mileage, year, engine and other categorical dummies (brands) Preview

Lets do some more analysis

  • For 1% in mileage, the price decreases by 0.11%
  • For each unit (litre) increase in Engine volume, log price increase by 0.14
  • For each extra unit (litre increase) of volume log increases by 0.14 and price increases by 15% Preview
  • When year increases by 1 year the log price increases by 0.04 and price increase by 4%
  • Solved sheet Refer Here

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