House Rent Analysis with Linear Regression Model—— A Case Study of Six Cities in India

Abstract

House rent in India has been rising significantly ever since the pandemic hit the country. In situations like this, it is important for consumers to have the concept of a reasonable rent price, as otherwise, they may suffer from landlords raising rents deliberately. To resolve this issue, a prediction model for rent prices is necessary. This study analyses rent data from six cities (Kolkata, Mumbai, Bangalore, Delhi, Chennai and Hyderabad) in India with multiple variables, including size, furnishing status, and the number of bathrooms, bedrooms, halls, and kitchens and creates a prediction model based on the data. The main analytical methods used are linear regression and logarithmic transformation. This study also includes a general factor analysis based on the data. The results suggest that this model is reasonably accurate for reference uses, but needs further improvements if it is to be used commercially.