AP Statistics: Unit 3

Sample

Sample

who the data is collected from

Population

the entire group attempting to collect data from

Retrospective

looking at past data

Prospective

looking at data over multiple days/month/years

Generalization

to generalize about a population based on one study; can only be done is all participants are randomly selected/sampled; rare

Causation

casual relationship between two events; one caused another to happen

Experiment

treatments are imposed

Observational study

treatments are not imposed

Simple Random Sample

1.) Define the population

2.) Choose your sample size

3.) List the population

4.) Assign numbers to the units

5.) Find unique random numbers

6.) Select the samp

Stratified Random Sample

1.) Define the strata (homogenous groups) needed

2.) Define the sample size needed

3.) Randomly select from each strata

4.) Review and combine results

Cluster Sample

1.) Define the populations

2.) Divide into clusters (heterogenous groups)

3.) Randomly select (a) cluster(s) to use as the sample

Systematic Sample

1.) Decide a sample size

2.) Randomly select a number

3.) Choose every nth subject starting from that number (n)

Convenience Sampling

Only surveying those “easy to reach”

Voluntary Response Sample

Allows people to choose to be in the sample by responding to a general invitation; self-selecting

Wording Bias

When questions are worded in a way that persuades the responder

Non-Response Bias

When an individual refuses to respond/participate

Response Bias

When there is a systematic pattern of inaccurate answers to a survey question; lying

Undercovering

When some members of the population are less likely to be chosen or cannot be choses

Single Blinding

Either the subjects or the people who interact with them do not know which treatment a subject is recieving

Double Blinding

either the subjects nor those who interact with them do not know which treatment a subject is receiving

Placebo

Treatment that has no active ingredient, but is otherwise like other treatments; control group

Placebo effect

Describes the fact that some subjects in an experiment will respond favorably to any treatment, even an inactive treament

Experimental units

Unit to which a treatment applies; who is the experiment on; subjects

Control group

Used to provide a baseline for comparing the effects of other treatments; does not have to be a control group

Confounding Variable

a variable related to the explanatory variable and influences the response causing a misconception of the two being associated

Factor

a categorical explanatory variable

Levels

values of a factor

Treatment

a particular combination of values for the factors

Comparison

compare 2 or more treatments

Random Assignment

randomly assigns experimental units to treatments

Control

keep all other variable that might affect the response the same for all groups

Replication

use as many experimental units as possible in each group

Completely randomized experiment

assigns experimental units to the treatments strictly by chance; random half are to do one treatment and the other are to do other

randomized block design

separates experimental units into groups based on some homogenous characteristic and then randomly assigned treatments within each block

matched pairs design

creates blocks by matching pairs of similar experimental unit; the pair can be just one person doing both experiments seperately