PSYC 217 Lecture Notes - Lecture 1: Sample Size Determination, Central Tendency, Squared Deviations From The Mean
Document Summary
When describing data, we want to see what"s happening in the middle of the data. To accomplish this, we look at measures of ? . Whenever you have outliers, making the mean inaccurate (not re ective of the actual sample) and mode is readily observable. Whenever you have outliers, making the mean inaccurate (not re ective of the actual sample) no mode is readily available. Con: affected by outliers (i. e. , extreme scores) With increasing sample size, each extreme score has less effect on the mean. Has mathematical properties that allow us to do analyses. The moral of this tory: check for outliers if you only have a small sample, but try to get a large sample as rst step. Variability: the spread of distribution of scores. Sum of squared deviations around mean divided by n-1. Standard deviation (s or sd) = square root of s^2. On average, the deviations of each score from the mean.
