PSY 230 Lecture Notes - Lecture 4: Standard Score, Statistical Inference, Standard Deviation

• School: University of Arizona
• Department: Psychology Main
• Course: PSY 230
• Professor: Adam Lazarewicz

Document Summary

Lecture outline #4: z scores and the normal distribution. Inferential statistics: statistics that allow us to make more general statements, beyond the specific sample we studied. Z score: number of standard deviations that a score is above/below the distribution mean. Transforms raw score better description of score"s location in distribution. Allows you to compare score to normal population how to interpret z scores: If z < 0: score is less than mean. If z > 0: score is greater than mean. If z = 0: score is equal to mean. If z = 1: score is 1 standard deviation above mean. If z = 2: score is 2 sd above mean. If z = -1: score is 1 sd below mean. If z = -2: score is 2 sd below mean formula to convert raw score to z score: Sd: standard deviation step 1: figure out your deviation score (x-m) step 2: divide by standard deviation.