• Nikhil Sharad Giramkar

Mileage is one of the most important factors for working class people while buying a new four-wheeler. There are certain factors which the engineers consider while manufacturing the vehicle. The design has a huge impact on mileage; hence they claim the mileage of their vehicles by keeping certain factors in their mind. In this paper, multivariable regression analysis has been done on a dataset consisting of specifications of four-wheeler petrol variant cars to predict the elements which affect the mileage in km/l. Descriptive statistics of all these elements has been provided. Pearson’s correlation among them has also been established. A linear regression model with best fit has been applied on the collected sample. A regression equation has also been obtained which represents the model. Interpretation from the analysis and discussion of results has also been provided at the end.

Car, Mileage, Variables, Multivariable regression, Regression model, Pearson’s correlation

"Multivariable Regression Analysis for prediction of factors affecting car mileage", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 9, page no.1258-1263, September-2020, Available :http://www.jetir.org/papers/JETIR2009171.pdf

"Multivariable Regression Analysis for prediction of factors affecting car mileage", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 9, page no. pp1258-1263, September-2020, Available at : http://www.jetir.org/papers/JETIR2009171.pdf