STAT 101 Lecture Notes - Lecture 3: Standard Deviation, Normal Distribution, Standard Score

• School: Simon Fraser University
• Department: Statistics
• Course: STAT 101
• Professor: Harasha Perera

Document Summary

We now have a toolbox of graphical and numerical methods for describing distributions. What is more, we have a clear strategy for exploring data on a single quantitative variable. They both lie at the center of the curve. The mean of a skewed curve is pulled away from the median in the direction of the long tail. Changing without changing moves the normal curve along the horizontal axis without changing its variability: the standard deviation controls the variability of a normal curve. Any particular normal distribution is completely specified by two numbers: its mean and standard deviation: the mean of a normal distribution is at the center of the symmetric normal curve. The standard deviation is the distance from the center to the change-of-curvature points on either side. In the normal distribution with mean and standard deviation : Approximately 68% of the observations fall within of . Approximately 95% of the observations fall within 2 of .