Need assistance with this statistic problem - (in excel format)
"Lies, damned lies, and statistics" is a phrase describing the persuasive power of numbers, particularly the use of statistics to bolster weak arguments, and the tendency of people to disparage statistics that do not support their positions. It is also sometimes colloquially used to doubt statistics used to prove an opponent's point.
The term was popularized in the United States by Mark Twain (among others), who attributed it to the 19th-century British Prime Minister Benjamin Disraeli (1804-1881): "There are three kinds of lies: lies, damned lies, and statistics." However, the phrase is not found in any of Disraeli's works and the earliest known appearances were years after his death. Other coiners have therefore been proposed. The most plausible, given current evidence, is Englishman Sir Charles Wentworth Dilke (1843-1911).' (http://en.wikipedia.org/wiki/Lies,_damned_lies,_and_statistics)
The (entirely fictitious) University of South Central Texkansahomatucky (USCT) is being sued for sexually discriminatory hiring practices. Last year, they hired two classes of employees, administrative staff and academic staff. They received 750 applications from women for administrative staff positions, of which they hired 250, and 250 applications from women for academic positions, of which they hired 200. In total, then, they had 1000 applications from women of which they hired 450, or 45%. They received 300 applications from men for the administrative positions, of which they hired 75, and 700 applications from men for the academic positions, of which they hired 550. In total, of the 1000 applications they received from men, they hired 625, or 62.5%.
Based on the numbers presented, what do you think of the discrimination claim?
The first impression that you can deduce from the data is that women are discriminated in favor of the men in hiring. A close scrutiny will show that generally there are more males hired (62.5%) than females (45%). However, a close ...
The solutions shows that statistical data can be deceiving and should not be taken on its face value. Additional information must be considered before conclusions are made.