STAT 301 Lecture Notes - Lecture 5: Squared Deviations From The Mean, Standard Deviation, Descriptive Statistics
Document Summary
The same variance, or just variance , is a very common measure of dispersion. Unlike the range or iqr, the variance is computed using all of the data values. As a result, it is more sensitive to outliers. The sample variance is denoted as s2. To calculate variance, we first need the sum of squared deviations (called ss, for sum of squares ) Deviation = difference between one observation and the mean xi- mean. Squared deviation = the deviation of an observation, squared (xi mean)2. Ss= the sum of the squared deviations for all observations. The sample standard deviation or just standard deviation is the square root of the sample. We use the letter s to denote it. The standard deviation is what it sounds like: a standardized amount by which the observations deviate from the mean. It"s kind of like a weird average deviation from the mean. Large standard deviation implies data are highly dispersed, or spread out.
