AP Statistics Chapter 4: Collecting Data Vocabulary

Population

the entire group of individuals we want information about

Sample

subset of individuals in the population from which we collect data

Census

collects data from EVERY individual in the population

Sample Survey

A study that collects data from a sample to learn about the population from which the sample was selected

Convenience sampling

selects individuals from the population who are easy to reach

Bad Sampling:

-Produces unrepresentative data

-favors certain outcomes over the others(bias)

Bias

the systematic favoring of certain outcomes over others in a study

-it is very likely to underestimate or very likely to overestimate the value you want to know

-not just bad luck, but rather bad study design

Voluntary Response sampling

allows people to choose to be in the sample by responding to a general invitation

Bad Sampling:

-attracts people who feel strongly about an issue

-leads to bias

Random Sampling

involves using chance process to determine which members of a population are included in the sample

Simple Random Sampling(SRS)

size n is chosen in such a way that every group of n individuals in the population has an equal chance to be selected as the sample

-sample without replacement

Stratified Sampling

selects a sample by choosing an SRS from each stratum and combining the SRSs into one overall sample

-works best when the individuals within each stratum are similar(homogeneous)

Strata

groups of indiviudals in a population who share charactersitics thought to be associated with the variables being measured in a study

Cluster

a group of individuals in the population that are located near each other

Cluster Sampling

selects a sample by randomly choosing clusters and including each member of the selected clusters in the sample

-save time and money

-individuals within each cluster are heterogeneous (mirroring the population)

-clusters similar to each other in composition

Systematic random sampling

selects a sample from an ordered arrangement of the population by randomly selecting one of the first k individuals and choosing every kth individual thereafter

- if there are patterns in the way population is ordered that coincide with the pattern in a systematic sample, the sample may not be representative of the population

Undercoverage

occurs when some members of the population are less likely to be chosen or cannot be chosen in a sample

Nonresponse

occurs when an individual chosen for the sample can't be contacted or refuses to participate

Response bias

occurs when there is a systematic pattern of inaccurate answers to a survey question

-basically respondents lie

Observational Study

observes individuals and measures variables of interest but does not attempt to influence the responses

Response variable

measures an outcome of a study

Explanatory variable

may help explain or predict changes in a response variable

Confounding

occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other

Experiment

deliberately imposes treatments (conditions) on individuals to measure their responses

Placebo

a treatment that has no active ingredient, but is otherwise like other treatments

Treatment

a specific condition applied to the individuals in an experiment

Experimental unit

object to which a treatment is randomly assigned

Subjects

when the experimental units are human beings

Factor

an explanatory variable that is manipulated and may cause a change in the response variable

levels

different values of a factor

Control Group

-used to provide a baseline for comparing the effects of other treatments

-depending on the purpose of the experiment, a control group may be given an inactive treatment (placebo), an active treatment, or no treatment at all

Placebo effect

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

Double blind

neither the subjects nor those who interact with them and measure the response variable know which treatment a subject is receiving

Single Blind

either the subjects or the people who interact with them and measure the response variable dont know which treatement a subject is receiving

Random assignment

experimental units are assigned to treatments using chance process

-doing so helps create roughly equivalent groups of experimental units by balancing the effects of other variables among the treatment groups

Control

keeping other variables constant for all experimental units

Replication

giving each treatment to enough experimental units so that a difference in the effects of the treatments can be distinguished from chance variation due to the randome assignment

Comparison

Use a design that compares two or more treatments

Completely randomized design

the experimental units are assigned to the treatments completely at random

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

Randomized Block Design

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

Matched Pairs Design

common experimental design for comparing two treatments that uses blocks of size 2. In some matched pairs designs, two very similar experimental units are paired and the two treatments are randomly assigned within each pair.

-Each experimental unit receives both treatments in a random order

Sampling Variablility

refers to the fact that different random samples of the same size from the same population produce different estimates

Statistically Significant

When the observed results of a study are too unusual to be explained by chance alone

-not due to chance