Psychology Statistics

statistics

characterizes a sample

parameter

characterizes a population

sample

subset of observations from the population of interest

population

ALL participants

descriptive statistics

help us organize and summarize data

inferential statistics

draw conclusions about populations based on sample data

independent variable

used to describe/explain DV differences or cause the DV changes

dependent variable

outcome of interest in an experiment, what we measure

extraneous variables

variables (not the IV) that impact the DV, interfere with our findings

quantitative

tells about amount or degree of variable

qualitative

tells if things are different or the same but not amount

nominal

categorize people/subjects into groups, groups usually have a title

ordinal

NOT equal intervals
(ex. educational level, place in a contest, standing in graduation class)

interval

equal intervals, categorize, rank order

bar graph

set of NONadjoining rectangles whose heights represent frequency values, NOMINAL data

histogram

Set of ADJOINING rectangles whose heights represent the frequency of their values; QUANTITATIVE data

frequency polygon

Series of dots whose heights represent the frequency of values connected by a line; QUANTITATIVE data

positive skew

mean>median

negative skew

mean

central tendency

single score representing the entire data set and it helps us interpret single scores (ex. mean, mode, range)

variability

a way of summarizing how spread out the scores in a distribution are

mode

most commonly occurring score

median

value that divides a distribution into two equal halves

mean

arithmetic average

μ

mean for a population

x̄

mean for a sample

correlation

quantify the strength and direction of the relationship between two variables

spurious

artificially high or low

empirical

based on actual scores

generalizability

can apply findings from one sample or context to others

random sample

subset of a population chosen so that all samples of size N have an equal opportunity of being selected

correlational studies

participants come with their group membership (ex. # of pets, political affiliation, gender)

Sampling distribution

distribution of sample statistics

Frequency distribution

distribution of individual scores

conceptual hypothesis

general statement about the relationship between the IV and DV or about the magnitude of a relationship

statistical hypothesis

hypothesis written in mathematical notation

null hypothesis

assumes there is no relationship/difference/effect

1 tailed test vs 2 tailed test

type I error

rejecting a true null

type II error

retaining a false null

matched pairs

the experimenter made the matches (ex. basketball dunking)

repeated measures

same participants are tested twice