AP Stats Ch. 4

Population

Entire group we want information about

Census

collects data from every individual in the population

Sample

subset of the population from which we collect data

sample survey

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

Conveince Sample

Selecting people from the population that are easier to reach

Bias

A study that is likely over or underestimate the true data

voluntary response sample

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

random sampling

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

simple random sample (SRS)

of size n consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be the sample actually selected

sampling without replacement

an individual can only be selected once

sampling with replacement

an individual from a population can be selected more than once

Strata

Groups of individuals in a population that are similar in some way that might affect their responses.

stratified random sampling

choosing an SRS from each strata combining the SRSs into one overall sample.

cluster

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

Systematic random sampling

randomly choose one person and survey them and every kth person after them

Cluster sampling

randomly select a cluster and survey everyone in the clusters

Undercoverage

occurs when some groups in the population are left out of the process of choosing the sample

Nonresponse

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

response bias

systematic pattern of inaccurate answers to a survey question

observational study

observes individuals and measures variables but does not influence the response

response variable

measures the outcome of a study

explanatory variable

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

confounding

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

Experiment

A research method in which an investigator manipulates one or more factors to observe an outcome

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

the object to which a treatment is randomly assigned

subject

experimental unit that is a person

factor

a variable that is manipulated and may cause a change in the response variable (usually used when talking about multiple variables)

levels

the specific values that the experimenter chooses for a factor (ex. yes or no, or 10th grade, 11th grade, or 12th grade)

Control group

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

placebo effect

some subjects will respond to any treatment, even if inactive

double-blind

neither the subject nor person administering experiment knows what treatment the subject is getting.

single-blind

An experiment in which either the subjects or those who interact with them and measure the response variable, but not both, know which treatment a subject received.

random assignment

assigning participants to experimental and control conditions by chance, thus minimizing preexisting differences between those assigned to the different groups

control (similar to control group)

keeping other variables constant

replication

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

4 principles of experimental design

1. Comparison

2. Random Assignment

3. Control

4. Replication

Completely randomized design

units are assigned to 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

random assignment is carried out within each block

Matched pairs design

experimental design that uses blocks of size of two

sampling variability

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

statistically significant

an observed effect so large that it would rarely occur by chance

Experiment - causation Sample/survey - inference

what shows causation and what allows inferences