Q3. In this exercise you’ll use R package tidyverse (see chapter 4 of Introduction to Data Science Data Analysis and Prediction Algorithms with R by Rafael A. Irizarry. You need to go through chapter

Q3. In this exercise you’ll use R package tidyverse (see chapter 4 of Introduction to Data Science Data Analysis and Prediction Algorithms with R by Rafael A. Irizarry. You need to go through chapter 4 before attempting the following questions. Using dplyr functions (i.e., filter, mutate ,select, summarise, group_by etc. ) and “murder” dataset (available in dslab R package) and write appropriate R syntax to answer the followings: a. Calculate regional total murder excluding OH, AL, and AZ (Hint: filter(! abb %in% x) # here x is the exclusion vector) b. Display the regional population and regional murder numbers. c. How many states are there in each region? (Hint: n ()) d. What is Ohio’s murder rank in the Northern Central Region (Hint: use rank(), row_number()) e. How many states have murder number greater than its regional average (Hint: nrow() ) f. Display 2 least populated states in each region (Hint: slice_min() ) Use pipe %>% operator for all the queries. Show all the output results

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