Applied Regression analysis & generalized linear models

Auto-mpg analysis: The data file auto-mpg.data is avaliable at https: //archive.ics.uci.edu/m1/datasets/auto+mpg, and includes gas mileage info for a variety of cars from the 1980s, in addition to other features. In this problem we consider that 'mpg' is the response variable of interest. The attributes are (see read me file as well): (a) Exploratory Data Analysis (EDA): Prepare scatterplots, boxplots, pairs plot with smoothing lines, co-plot, density estimators plot. Discuss what you observe. (b) Carry out an Ordinary Least Squares analysis with gas mileage as response variable and other features as explanatory variables (and include an intercept). Write an OLS program (your own code) using linear algebra as discussed in class. Your output should include: the coefficient estimates, the residual sum of squares, the SSreg, and the R^2. How do your results compare with those provided by the function lm()? (c) Create a residual versus fitted plot from the regression above. Discuss. Are there any outliers? (d) What can you conclude from your overall analysis? Auto-mpg analysis: The data file auto-mpg.data is avaliable at https: //archive.ics.uci.edu/m1/datasets/auto+mpg, and includes gas mileage info for a variety of cars from the 1980s, in addition to other features. In this problem we consider that 'mpg' is the response variable of interest. The attributes are (see read me file as well): (a) Exploratory Data Analysis (EDA): Prepare scatterplots, boxplots, pairs plot with smoothing lines, co-plot, density estimators plot. Discuss what you observe. (b) Carry out an Ordinary Least Squares analysis with gas mileage as response variable and other features as explanatory variables (and include an intercept). Write an OLS program (your own code) using linear algebra as discussed in class. Your output should include: the coefficient estimates, the residual sum of squares, the SSreg, and the R^2. How do your results compare with those provided by the function lm()? (c) Create a residual versus fitted plot from the regression above. Discuss. Are there any outliers? (d) What can you conclude from your overall analysis