3. The data in oxygencsv are 100 measured daily purities of oxygen delivered by a single supplier. The 1values are in hundredths of a percent purity above 99.00% (so 63 means 99.63%). The supplier's lower specication limit (lowest acceptable value) is 99.50%. (The data are taken om D. C. Jacobs (1990), Watch Out for Nonnorrnal Distributions, Chemical Engineering Progress.) a. Make a time-sequence plot for the data. Are there any obvious time trends? What would be the practical usefulness of early detection of any such time trend? b. Ignore the time order of the data collection and represent these data with a histogram. Describe the \"shape" of the data, including symmetry and outliers. c. Calculate the mean, standard deviation, and ve-number summary. Which statistics would you choose to summarize this data set and why