STAT151 Lecture Notes - Lecture 6: Probability Plot, Frequency Distribution, Inflection Point

• School: University of Alberta
• Department: Statistics
• Course: STAT151
• Professor: Omar Rivasplata

Document Summary

Expressing a distance from the mean in standard deviations standardizes the performances. To standardize a value, we subtract the mean and then divide this difference by the standard deviation (s): We call the resulting values standardized values , denoted as z. A negative z-score tells us that the data value is below the mean. A positive z-score tells us that the data value is above the mean. They can also be called z-scores z-scores measure the distance of a data value from the mean in standard deviations. A z-score of -1. 3 is more extraordinary than a z-score of 1. 2. A z-score of 2 says that a data value is two standard deviations above the mean. o o o o. Using the standard deviation as a ruler to measure statistical distance from the mean, we can compare values from the same data set, or even two values measured on different variables or with different scales.