stat1 quiz1

data

information collected about individuals or objects

variable

a characteristic we measure or observe

statistics

using data to describe, learn, and make decisions

before trusting a statistic, ask:

what was measured?, why was the data collected?, how was it collected?

population

the entire group that we want info about

sample

the part of the population we actually examine to gather info about the population

observational study

a study based on data in which no manipulation of factors has been employed

experimental study

the researcher manipulates one of the variables and tries to determine how the manipulation influences other variables

census

the official count of a population

convenience sample

choosing individuals who are easiest to reach; "easiest/nearby"

voluntary response sample

people decide for themselves whether to participate; "self-selected"

Simple Random Sample (SRS)

every possible sample of size n has an equal chance of selection; "random from whole population"

stratified random sample

split into similar groups (strata), take an SRS from each, then combine; "some from every group"

cluster sample

split into groups (clusters), randomly choose clusters, include everyone in chosen clusters; "all from selected groups"

Systematic Random Sample

choose a random start, then select every kth member; "every kth"

bias questions

1. who chose to respond? 2. who was left out? 3. who did not answer 4. could the answers be distorted?

voluntary response bias

people with strong opinions may be overrepresented

undercoverage bias

some groups had little or no chance to be selected

nonresponse bias

selected individuals could not be contacted or refused

response bias

wording, timing, memory, social desireability, interviewer effects, or guessing can change responses

how to select an SRS

1. label 2. randomize 3. skip 4. stop

experimental units

the individuals on which the experiment is done

subject

a human experimental unit

treatment

a specific condition applied to the individuals in an experiment

explanatory variable

a variable that we think explains or causes changes in the response variable

response variable

measures an outcome of a study

factor

the explanatory variables in an experiment

level

the various groups the factors take

4 elements of experimental design

comparison, randomization, control, replication

Placebo

dummy treatment

placebo effect

experimental results caused by expectations alone; any effect on behavior caused by the administration of an inert substance or condition, which the recipient assumes is an active agent.

Blinding

a technique where the subjects do not know whether they are receiving a treatment or a placebo

double blind

when neither researchers nor participants are aware of who' receives the treatment

confounding variable

a factor other than the independent variable that might produce an effect in an experiment

lurking variable

a variable that is not among the explanatory or response variables in a study but that may influence the response variable

completely randomized design

the treatments are assigned to all the experimental units completely by chance

matched pairs design

Participants are matched on key characteristics. One participant does control condition and the other does the experimental condition.

Block Design

the random assignment of units to treatments is carried out separately within each block

block

a group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments

Inference

A conclusion one can draw from the presented details.

random selection of individuals

allows inferences for the population

random assignment in an experiment

permits inference about cause and effect

representative sample

randomly selected sample of subjects from a larger population of subjects

strata

groups of similar individuals

sampling error

an error that occurs when a sample somehow does not represent the target population

non-sampling error

occurs when the sample data are incorrectly collected, recorded, or analyzed

generalization

Extending sample results to the population from

which the sample was selected.

causation

A conclusion that changing one variable produced a

change in another

association

A relationship in which two variables tend to vary

together. Association alone does not establish

causation

comparison

Using two or more treatment conditions so their

responses can be compared

Treatment combination

A treatment formed by combining one level from each

factor when an experiment has multiple factors.