Statistics

Statistics

descriptive statistics: ways to describe larger amounts of data (graphs, tables)
inferential statistics: generalizing beyond experimental measures
population: all individuals of interest to a study
sample: a representative set of individuals from pop.
random sampling + random assignment
observational studies * compare 2 variables to determine if a relationship exists * does not prove causation * not manipulated by experimenter
confounding variables
experimental studies * independent variable: experimenter changes * dependent variable: experimenter measures
histograms * positive skew (to the left) * negative skew (to the right) * normal
central tendencies: central point of distribution * mean * use median if distribution is skewed / has outliers * use mode when describing shape of distribution
variability: how scattered the scores are around the central point * range * interquartile range * standard deviation * mean, find distance from mean, square it * multiplying by a constant will multiple sd by that constant * variance: sd^2
SS: sum of squared deviations
degrees of freedom: number of scores free to vary * sample variance: ss / n-1 * population variance: ss / n

\ \n