In this exercise, we will apply the multinomial logistic model to individual-level discrete choice data. The goal is to learn how to format the data, apply the R package "mlogit" to fit a multinomial logistic model and interpret the results. The setting of the exercise is about consumers' choices of shopping malls. Please download the data file "Mall_choice_data.csv" from Canvas. Use read.csv( ) to read the data into R as a data frame. In this dataset, each of the 500 consumers from a same city chooses a shopping mall to visit every week for a period of 12 weeks. There are 4 different shopping malls and a consumer also has the option of electing not to visit any of them in a week. Hence, the choice set is denoted as {1, 2, 3, 4, 0}, where 1 through 4 are the ID's of the 4 malls and 0 means not visiting any of them (often called the outside option in a choice model). The columns in the dataset are as follows.