The normal curve is the shape that represents how variables are distributed, and it has some very interesting characteristics: a) the mean, the median, and the mode are all the same value; b) it is symmetrical about its midpoint, which means that the left and right halves of the curve are mirror images; and c) the tails of the curve get closer and closer to the X-axis but never touch it—the curve is asymptotic (Salkind, 2012). In fact, many inferential statistics are based on the assumption that the population distribution of variables from which samples are selected is normal in shape. From a practical standpoint, how likely is a healthcare professional conducting an informal study or program evaluation at their organization to achieve a “normal distribution curve”?
Salkind, N. J. (2012). Exploring research. (8th ed.). Upper Saddle River, NJ: Pearson
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