I really need help on this problem as I am fairly new at programming in R. Here is the CSV file that is used in the problem

https://drive.google.com/open?id=1luhfDrhfUgxy04iHgBXopguV3UxE1teV

Problem 1 (Chess ratings) The ChessRatingComparison.csv file on the class website contains self-reported chess rat ings from Chess.com. The dataset has ratings from Chess.com, USCF (United States Chess Federation) and FIDE (the World Chess Federation). Bullet and blitz are different versions of fast chess The goal of this problem is to determine the relationship between the other variables and the USCF regular rating. Turn in your code as an appendir to the following problem. (a) Produce a pairwise scatterplot of the data, and describe the visual relationships be- tween the variables. Be sure to put the USCF regular rating as the top row (b) Write down a simple statistical model for the relationship between USCF regular rating and Chess.com live standard rating. Using the full dataset, fit your model, providing OLS estimates of your regression parameters. Additionally report 95% confidence intervals, t-statistics and relevant p-values. Are your estimated parameters significantly different from zero? c) Provide some relevant diagnostic plots for your model. Discuss the results -is the model adequate, is there evidence of outliers, are there high leverage data points, etc.? d) If there are outliers in the data, remove them and redo part (b) (providing all of the same estimates/discussion as in part (b)). Why are particular data values outliers? e) Interpret your parameter estimates and results from part (b)/(d) in words (f) If your professor were a chess player, his Chess.com standard rating would probably be about 1600 (a guess based on tactic exercises). What would the average 1600-rated player on Chess.com rate as in the USCF rating system (be sure to include confidence bounds)? Additionally predict your professor's USCF rating (with confidence bounds) (g) How would you decide which of the other rating systems provides best predictions for USCF regular ratings? Fit some relevant models and provide an defensible explanation for your solution