Statistics
University/Undergrad
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