In order for the test to show normal distribution, there must be enough test subjects. For example, in order to find out where I would be on the bell curve, one would need to test a number or women regarding their shoe size. There have been several studies that show the average size of height for women is between 5’3’’ and 5’6’’. The average shoe size for women is 8-9. My shoe size is 10-11 depending on the shoe and I am 5’10’’. Clearly I am not in the middle of the bell curve as I am much taller than the average woman. Things that also must be taken into consideration are that shorter individuals usually have smaller feet and taller individuals have larger and longer feet. This may affect the end result depending on the height of the women tested. When looking at the bell curve, one must determine where the numbers came from and if there were any characteristics that are not normally distributed. According to our text, Cohen & Swerdlik (2010) state that “the normal curve is a bell-shaped, smooth, mathematically defined curve that is highest at its center. From the center it tapers on both sides approaching the X-axis asymptotically (meaning that it approaches, but never touches, the axis)” (p. 93). It is important to understand what the bell curve in when conducting measurements and statistics; this will give the tester the norms, the unusual, and the highest percentile information on the test being given.
Some characteristics that may affect the test would not normally be distributed. For example, Women with health issues may have different variables for the height and shoe size. The ages of the women are also a definite factor.
Reference:
Cohen, R. J. & Swerdlik, M. E. (2010). Psychological testing and assessment: An introduction to tests and measurement (7th ed.). New York: McGraw Hill.
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