Lecture 7 Outline of Last Lecture I Samples and Population Psych 311 1st Edition Outline of Current Lecture I Perposes of Determining Z Scores II Location within Distribution III Standardized Distributions IV Percentile Scores Current Lecture I Perposes of Determining Z Scores Determine location of raw score X within distribution Standardizing disrtibutions making 2 different distributions the same in terms of their mean and SD Z Score formula Z X II Location within Distribution Z scores can specify location Info provided by Z scores sign or and number value of z score sign tells you where the score falls relative to mean is above mean is below number value tells you how far score falls from mean in units of SD the larger the value the further from the mean Z X numerator distance from mean determines sign of score denominator unit Z score tells you how far score falls from the mean in units of SD III Standardized Distribution A distribution composed of raw scores transformed into z scores Z Distribution standardized distribution Properties of Z Distribution The mean will ALWAYS be Zero Standard deviation will ALWAYS be 1 0 These notes represent a detailed interpretation of the professor s lecture GradeBuddy is best used as a supplement to your own notes not as a substitute The shape will ALWAYS be identical to the shape of the raw distribution SD 1 0 because 1 SD above the mean would end up being SD SD 1 0 Advantage to standardizing distributions is that they transform distributions to make comparisions between two unalike sets of data IV Percentile Scores Each section under distribution represents percent of entire distribution Disadvantages of Standard scores Z scores expressed relative to sample difficulty in interpretation dependent on sample distribution Transform Z distribution to distribution with predetermined mean and SD Extreme Scores are scores that have a Z distribution beyond 2 from the mean in either direction
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