The profession of soldiering as part of a military is older than recorded history itself. Some of the most enduring images of the classical antiquity portray the power and feats of its military leaders. The Battle of Kadesh in 1274 BC was one of the defining points of Pharaoh Ramses II's reign, and is celebrated in bas-relief on his monuments. A thousand years later, the first emperor of unified China, Qin Shi Huang, was so determined to impress the gods with his military might, he was buried with an army of terracotta soldiers. The Romans were dedicated to military matters, leaving to posterity many treatises and writings, as well as a large number of lavishly carved triumphal arches and victory columns.
A century or so later, in the hands of writers such as Jean Froissart, Miguel Cervantes and William Shakespeare, the fictional knight Tirant lo Blanch, and the real-life condottieri John Hawkwood would be juxtaposed against the fantastical Don Quixote, and the carousing Sir John Falstaff. In just one play, Henry V, Shakespeare provides a whole range of military characters, from cool-headed and clear-sighted generals, to captains, and common soldiery.
Examinees also receive a score on what is called the Armed Forces Qualification Test (AFQT). AFQT scores are computed using the Standard Scores from four ASVAB subtests: Arithmetic Reasoning (AR), Mathematics Knowledge (MK), Paragraph Comprehension (PC), and Word Knowledge (WK). AFQT scores are reported as percentiles between 1-99. An AFQT percentile score indicates the percentage of examinees in a reference group that scored at or below that particular score. For current AFQT scores, the reference group is a sample of 18 to 23 year old youth who took the ASVAB as part of a national norming study conducted in 1997. Thus, an AFQT score of 90 indicates that the examinee scored as well as or better than 90% of the nationally-representative sample of 18 to 23 year old youth. An AFQT score of 50 indicates that the examinee scored as well as or better than 50% of the nationally-representative sample.