Volume I - Section VI - Statistical Analysis 
Page VI - 1 
6. STATISTICAL ANALYSIS 
6.1 Introduction to Tests of Significance 
The normal distribution of individual scores and the understanding of standard deviation are key 
elements to understanding significance tests. Therefore, a brief review is in order. 
6.1.1 Mean 
The mean is defined as the sum of scores divided by the number of scores. 
6.1.3 Standard Deviation 
The standard deviation is the square root of the average squared deviation from the mean. For 
example, the standard deviation of the Year 2 Internal Medicine scores was 7.1, therefore, we can 
conclude that 68 percent of the class fell within plus or minus 7.1 points of the mean. 
Additionally, we can conclude that 95 percent of the class fell within plus or minus 2 x 7.1 points 
of the mean. 
6.1.4 Z- Score 
The z-score, (score-mean)/standard deviation, is often used to express a score in relation to the 
mean score. Graphs of the normal curve usually depict z-scores along the abscissa of the graph 
and frequency along the ordinate. In the graph below, the shaded area of the normal curve 
represents five percent of the distribution. That is, 95 percent of the observations fall between z- 
scores of -1.96 and +1.96 or, put another way, five percent of the observations fall outside this 
range. 
Distribution of Individual Scores 
