5-5 Milestone Two: Data Validation and Discovery Summary: Perform the summary function to get the descriptive statistics from the file. Identify any noteworthy findings from this summary function and whether or not this changes your plan from Milestone One. Be sure to explain your rationale in either case. You must also submit either a screenshot or an export of the log of the execution of the command and its results. Variables: Use the same two of the data fields (i.e., columns) in the files that you selected to compare in Milestone One. For example, we can use Total Salary and Total Compensation fields in each file to compare Firefighter and Police. For each of the Firefighter and Police data, create three separate variables for each of the two fields selected. There will be a total of 12 variables created. The three separate variables will be the minimum, maximum, and average value for each of the data fields for each of the Firefighter and Police data files. Data Validation: Discuss your findings. You have now calculated the same information (the min, max, and average) in three different ways and places (Milestone One, the summary function, and the variables function). Do the calculations and commands you performed above confirm what you found in Milestone One? Why or why not? This is considered data validation. Did you find new avenues to pursue? Data Discovery: Now, assuming you have validated your data, compare the variables from Firefighter and Police. How do the num