From Data to Decision - Essay Example

Best Actors Best Actresses es Frequency 0 to 30 3 31 to 40 27 41 to 50 31 51 to 60 14 61 to 70 3 71 to 80 More 0 es Frequency 0 to 30 30 31 to 403041 to 501251 to 60261 to 70371 to 802More0Cumulative Frequencies33061757879Cumulative Frequencies306072747779The data presented above represents two separate data sets that deal with the best actors and best actresses that have been classified as per different classes. The classes created to represent the data have wide as well as narrow classification bands that are geared as multiples of ten.

The first class has the widest band being based between 0 and 30 while the other bands are classified in increments of 10 up to 80. One understandable reason for such classification is the small amount of data in this classification in the actors’ data set though this position is not justified in the actresses’ data set. The data sets have been graphed accordingly as histograms in the graphs presented below.The graphs presented above clearly show that the best actors in the range between 0 and 30 are only 3 which represent only 3.

8% of the entire data set. In contrasts the best actresses in this classification are 30 that represent 37.8% of the entire data set making it exceptionally high. Furthermore, as the classifications in the best actors categories proceeds the frequency increases most in the range between 31 and 60 with the greatest expansion in the range between 41 and 50 claiming a frequency of 31. In contrast, the best actresses graph tends to display the greatest frequencies between 0 and 41 with a total of 60.

This is out of a total of 79 which in turn makes that best actresses graph skewed towards these age ranges. In contrast the best actor graph is somewhat centrally distributed around the 41 to 50 classification.