Multinomial Logit models raw data for Chicago and Indianapolis

<p>This data was obtained from the National Household Survey for Chicago and Indianapolis (https://nhts.ornl.gov/). We processed this data to be able to estimate Multivariate logistic regressions. These models predict the relationships between dependent and independent variables. It calculates the probability of something happening depending on multiple sets of variables. For this project, we used this data and the modeling to understand these two cities' substitution or complementing trip patterns when analyzing bike, walk, public transit, and ridesharing use (as a proxy of shared autonomous vehicles). These four modes were our independent variables. The rest of the database was used as dependent variables or factors related to the probability of choosing those four modes of transportation in Chicago and Indianapolis. </p>