You have been hired to conduct business research for the purpose of identifying ways to improve fuel efficiency without disturbing consumer preference.Use the data presented to create a multiple regression model which explains the impact of the variables you selected on City and Highway fuel economy. (1) Make a frequency distributions and/or histograms for CityMPG and HwyMPG. Describe the distributions. (2) Create and discuss the descriptive statistics for all varables.Use tables to present measures of central tendencies and measures of dispersion for continous variables.Use tables, graphs, and charts to present frequencies and descriptives for nominal data.Be sure to identify, report, and recommend a treatment for any outliers. (3) Detimine if there is a statisticsally significant difference in CityMPG based on vehicle body style. Be sure to use Tukey's test to determine if all styles are different.Do the same for HwyMPG.Are the results the same for City and Hwy? (4) Create a scatter plot for X = Weight and Y = CityMPG. What does it suggest?Fit a simple regression on the scatter plot. Interpret the slope and fit. (5) Estimate a multiple regression model using CityMPG as the response variable (dependent variable) and several numerical or binary predictors of your choice.Caution: If you use binary predictors, be carefulto omit one of the binary predictors in each group (body style, drive type, transmission type)to avoid perfect multicollinearity. (6) Did your multiple regression model offer a substantially better fit than the simple regression in step (4)?