Please use R Programming for this question and take screenshots of R Code once you are finished.

Data to use for question 1: https://drive.google.com/file/d/18kGNrHUfgcVv2hMKqL5E05L40xCl6e1M/view?usp=sharing

a. Visualize the distributions of the variables in this data. \"too can choose bar graphs, histograms and density plots. Make appropriate choices given ea ch type of variables and be careful when selecting parameters like the number of bins for the histograms. Note the re are some numerical variables and some categorical ones. The ones labeled as a 'bool' are Boolean variables, meaning they are only true or false and are thus a special type of categorical. Checking all the Histributions with visualization and summary statistics is a typical step when beginning to work with new data. b. How apply normalization to some of these numerical distributions. Specically, choose to apply zscore to one, min-m ax to another, and decimal scaling to a third. Explain your choices of which normalization applies to which variable in terms of what the variable means. what distribution it starts with, and how the normalization will affect it. c. 'v'isualize the new distributions for the variables that have been normalized. what has changed from the previous visualization in step a? d. For oontl, create a new variable called oont1_bins that is a binned version of that variable. This cont 1_bins will have a new set of values like low, medium, high. Low ranges from -lnf to 25, Medium ranges from 25 to 4112], and High ranges from 4:] to Inf. Show this binned version cont1_bins along with the other data from the dataset. Assign numerical values to the bins using the bin-mean and show the result. e. Building on {d}, use cont1_bins to create a smoothed version of oont] and display the new distribution. How is this new distribution different than the previous distribution for oontl