AP Statistics Unit 1, Part II: Collecting Data

Observational Study

A study that observes individuals and measures variables of interest but does not attempt to influence the responses ("passive"). This is not good for explaining cause/effect because of confounding variables.

Population

The entire group of individuals we want information about.

Sample

A subset of individuals in the population from which we actually collect data.

Census

Collects data from every individual in the population. Attempts to contact every individual in the population.

Random Sampling

Using a chance process to determine which members of a population are chosen for a sample.

voluntary response sample

Sample which consists of people who choose themselves by responding to a general invitation.

Convenience Sample

Sampling technique where individuals are chosen from the population who are easy to reach .

Simple Random Sample (SRS)

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

Stratified Random Sample

Sampling technique where the population is first classified into groups of similar individuals. Then a separate SRS is chosen in each stratum and the SRSs are combined to form the sample.

Cluster Random Sample

Sampling technique where the population is first classified into groups of individuals that are located near each other (clusters). Then an SRS of the clusters is chosen. All individuals in the chosen clusters are included in the sample.

Systematic Random Sampling

Sampling technique in which every Kth case is selected from list of group.

Undercoverage

Bias which occurs when some members of the population cannot be chosen in the sample.

Nonresponse

Bias which occurs when an individual chosen for the sample can't be contacted or refuses to participate, and the responses of those who didn't or cannot respond would differ greatly from those who did

Response Bias

Bias which occurs when respondents give incorrect answers. This involves issues with the actual responses given.

Experimental Units

Individuals on whom the experiment is being performed.

Subjects

Participants (experimental units) that are human beings.

Treatment

An experimental condition applied to the units/subjects.

Explanatory Variable

Attempts to explain the observed outcomes.

Response Variable

Measures an outcome of a study.

Factors

The explanatory variables in an experiment (explains the response to treatment).

Levels

A specific value of a factor. (ex. 200mg given orally, or 15 degrees, 20 degrees, etc.)

Placebo

A dummy treatment that causes no harm. (ex. sugar pill)

Placebo Effect

Usually a positive or beneficial response is attributable to the patient's expectation that the treatment will have an effect.

Control

Keeping variables (other than explanatory) the same for all treatment groups to avoid confounding and reduce variability in the response variable.

random assignment

Using a chance process to allocate units/subjects to treatment groups

Replication

use enough experimental units in each group so that any differences in the effects of the treatments can be distinguished from chance differences between the groups

Completely Randomized Design

A basic comparative experiment. All experimental units are allocated at random among all the treatments. The treatments are assigned to all the experimental units completely by chance.

randomized block design

Divide subjects with similar characteristics into blocks, and then within each block, randomly assign subjects to treatment groups.

Matched Pair Design

Compares two treatments by comparing the response of two matched experimental units. Units are matched two ways: (1) Two different units/subjects matched based on similar characteristics (ex. Identical twins). (2) One subject/unit receives both treatments (ex. person paired with him/herself).

Single Blind

When either the subjects or the researchers do not know what kind of treatment has been received.

Double Blind

When neither the subjects nor the people administering the experiment know which treatment the subjects received.

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

a study in which researchers deliberately impose treatments on experimental units to measure their responses

Sample Survey

a study that asks questions of a sample drawn from some population in the hope of learning something about the entire population

retrospective observational study

A study that uses existing data for a sample of individuals.

prospective observational study

A study that tracks individuals over time.

sampling with replacement

an individual from a population can be selected more than once

sampling without replacement

an individual from a population can be selected only once

Strata

groups of individuals in a population who share characteristics 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

Bias

The design of a statistical study shows bias if it systematically favors certain outcomes.

comparison

use a design that compares two or more treatments

sampling variability

refers to 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

Parameter

numerical summary of a population

statistic

a numerical measurement describing some characteristic of a sample

blocks

groups of subjects with similar characteristics