AmesHousing dataset in RStudio

AmesHousing dataset in RStudio. Try to fit, interpret and evaluate a regression mode in RStudio by following next 15 steps.
-Load the Ames housing dataset.
-Perform Exploratory Data Analysis and use descriptive statistics to describe the data.
-Prepare the dataset for modeling by imputing missing values with the variable's mean value or any other value that you prefer.
-Use the "cor()" function to produce a correlation matrix of the numeric values.
-Produce a plot of the correlation matrix, and explain how to interpret it. (hint - check the corrplot or ggcorrplot plot libraries)
-Make a scatter plot for the X continuous variable with the highest correlation with SalePrice. Do the same for the X variable that has the lowest correlation with SalePrice. Finally, make a scatter plot between X and SalePrice with the correlation closest to 0.5. Interpret the scatter plots and describe how the patterns differ.
-Using at least 3 continuous variables, fit a regression model in R.
-Report the model in equation form and interpret each coefficient of the model in the context of this problem.
-Use the "plot()" function to plot your regression model. Interpret the four graphs that are produced.
-Check your model for multicollinearity and report your findings. What steps would you take to correct multicollinearity if it exists?
-Check your model for outliers and report your findings. Should these observations be removed from the model?
-Check your model for outliers.
-Attempt to correct any issues that you have discovered in your model. Did your changes improve the model, why or why not?
-Use the all subsets regression method to identify the "best" model. State the preferred model in equation form.
-Compare the preferred model from step 13 with your model from step 12. How do they differ? Which model do you prefer and why?