PSY201H1 Lecture Notes - Lecture 5: Standard Deviation, Standard Score, Normal Distribution
Document Summary
Psy201 lecture 5: z-scores location of scores & standardized distributions. = ss /n s = ss /(n 1) The standard normal distribution is a normal distribution with a mean equal to 0 and a standard deviation equal to 1. X-axis z-score units (standard distribution units) 50% of the area is above and 50% is below: nearly all area is between z = -3. 00 and z = +3. 00 (mean = median = 50th percentile) Z = z-score; x = score, = population mean, = standard deviation. Formula can also be rearranged to find and . We can make comparisons across different distributions because we standardized the distributions (transforming all scores into z-scores) that we"re dealing with. We can compare apples to oranges now! If the data being compared come from normal distributions, we can transform the data so two sets are equivalent standardization. A z-score distribution will always have a mean of zero (we take our original mean and.
