Stat Chapter 1 Flashcards

descriptive statistics

organize, summarize & communicate a group of numerical observations

• large amounts of data in a few #

inferential statistics

use sample data to make estimates about the larger population

• intelligent guesses

sample

set of observations drawn from population of interest

population

includes all possible observations about which we would like to know something

variables

observations of physical, attitudinal, & behavioral characteristics that can take on different values

discrete variables

take on only specific values - no other values can exist between #’s

continuous variables

take on a full range of values - an infinite #’s of values exist

nominal variables

for observations that have categories/names as values (always discrete)

• Australians = #1, New Zealanders = #2

ordinal variables variables

observations that have rankings as values (always discrete)

• TV shows

interval variables

for observations that have #’s as values; distance (interval) between pairs of consecutive #’s is assumed to be equal

ex: temperature

ratio variables

variables that meet the criteria for interval variables but have meaningful zero points

scale variable

variables that meets the criteria for an interval/ratio variable

level

a discrete value or condition that a variable can take on

ex: male is a level of the variable gender

predictor variable

at least two levels that we either manipulate/observe to determine its effects on the dependent variable

ex: which variable predicts the other?

outcome variable

the variable that we hypothesize to be related to/caused by changes in the predictor variable

ex: which variable is the outcome of the other?

confounding variable

any variable that systematically varies with the predictor variable so that we cannot logically determine which variable is at work

(also called confound)

reliability

refers to the consistency of a measure

validity

refers to the extent to which a test actually measures what it was intended for

• reliable does not equate to validity

hypothesis testing

the process of drawing conclusions about whether a particular relation between variables is supported by the evidence

operational definition

specifies the operations/procedures used to measure/manipulate a variable

ex: Billboard charts operationalize artist popularity

correlation

an association between two or more variables

• one way to test a hypothesis

independent variable

a type of predictor variable in which the researcher manipulates the levels of that variable

dependent variable

a type of outcome variable in which the researcher measures the response to the manipulation of the independent variable

random assignment

every participant in the study has an equal chance of being assigned to any of the groups, or experimental conditions in the study

experiment

a study in which participants are randomly assigned to a condition/level of one or more independent variables

experimental group

a level of the independent variable that receives the treatment/intervention of interest in an experiment

• one/two experimental groups are typically compared to a control group

control group

a level of the independent variable that does not receive the treatment of interest in a study. It’s designed to match an experimental group in all ways but the experimental manipulation itself

between-groups research design

participants experience one and only one level of the independent variable

ex: experiment that compares a control group w/an experimental group

within-groups research design

an experiment in which all participants in the study experience the different levels of the independent variable

ex: experiment that compares the same group of people before & after they experience a level of an independent variable

-within: experience one condition then must do all conditions

data ethics

a set of principles related to all stages of working with data - research design, data collection, statistical analyses, interpretation of analyses, and reporting of outcomes

open science

an approach to research that encourages collaboration, and includes the sharing of research methodology, data, and statistical analyses in ways that allow others to question and even try to recreate findings

replication

duplication of scientific results, ideally in a different context/with a sample that has different characteristics (also reproducibility)

3 data-related problems

replication failures, problems with data collection, old-fashioned statistics

severe testing

subjecting a hypothesis to rigorous statistical scrutiny aimed at uncovering any flaws in that hypothesis

preregistration

a recommended open-science practice in which researches outline their research design and analysis plan before conducting a study

HARKing

(H)ypothesizing (A)fter the (R)esults are (K)nown, is an unethical practice in which researches change their hypothesis to match their findings