Solution: Clean Data

library(dplyr)
clean_data <- function(x){
  # Code between the dashed lines 
  # ------
  result <- infert %>% mutate(case = as.logical(case))%>%   # Convert the `case` column into logical data type
    mutate(age_status = ifelse(age >= mean(age),'AA','BA'))%>%  # Create a new age column showing 'BA' if the age is below average otherwise it shows 'AA'
      filter(age_status =='BA' & case == TRUE & parity >= 4)%>%  # Filter the columns by the conditions
        select(age)%>%    # Select the `age` column
          sum()  # Calculate the total age
  # ------
  #Please name the desired output as 'result'
  cat(result)
}