MM207M4_Part2.docx 1.Across the USA, results for these exams are normally distributed. Wh

MM207M4_Part2.docx  1.Across the USA, results for these exams are normally distributed. What does that mean and why is this the case?  Since it is stated that the results are normally distributed this would mean the data is centered towards the mean and any score further away from that would have a less likely chance of happening.   2.If you were to create a histogram of all GRE scores, what would you expect the histogram to look like? Would it be symmetrical? Would it be bell shaped? How many modes would it likely have? Would it be skewed?  If we were to create a histogram for this normalized data it would be a symmetrical bell curve because of normal data distribution. This would also mean there should be one mode at the peak of the curve and it would not be skewed.  3.Suppose that the mean GRE score for the USA is 500 and the standard deviation is 75. Use the Empirical Rule (also called the 68-95-99.7 Rule) to determine the percentage of students likely to get a score between 350 and 650? What percentage of students will get a score above 500? What percentage of students will get a score below 275? Is a score below 275 significantly different from the mean? Why or why not?  Using the Empirical Rule we get the following:  68 percent of scores are within 500 – 75 = 425 and 500 + 75 = 575. (425-575)  Meaning that 68 percent of data must fall within 1 standard deviation of the mean.  95 percent of scores are within 500 - 2(75) = 350 and 500 + 2(75)= 650. (350-650)  Meaning that 95 percent of da