ap stats unit 3

Basic Principle for Designing Experiments

1. Random Assignment - Use chance to assign experimental units.

2. Replication - Use enough experimental units in each group so the differences can be distinguished from chance.

2. Control - Keep other variables that might affect the response the same for all groups. (This is not the same as control group.)

Bias

The design of a statistical study shows bias if it would consistently underestimate or consistently overestimate the value you want to know.

Census

A study that attempts to collect data from every individual in the population.

Cluster sample

To take a this type of sample, first divide the population into smaller groups. Ideally, these groups should mirror the characteristics of the population. Then choose an SRS of the groupes. All individuals in the chosen groups are included in the sample.

Completely randomized design

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

Control group

An experimental group whose primary purpose is to provide a baseline for comparing the effects of the other treatments. Depending on the purpose of the experiment, a control group may be given a placebo or an active treatment.

Convenience sample

A sample selected by taking the members of the population that are easiest to reach; particularly prone to large bias.

Double-blind

An experiment in which neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received.

Double-blind

An experiment in which neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received.

Experiment

Deliberately imposes some treatment on individuals to measure their responses.

Experimental units

The smallest collection of individuals to which treatments are applied.

Explanatory variable

A variable that helps explain or influences changes in a response variable. Also called factors.

Margin of error

A numerical estimate of how far the sample result is likely to be from the truth about the population due to sampling variability.

Nonresponse

Occurs when a selected individual cannot be contacted or refuses to cooperate; an example of a nonsampling error.

Observational study

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

Placebo

An inactive (fake) treatment.

Placebo effect

Describes the fact that some subjects respond favorably to any treatment, even an inactive one (placebo).

Population

In a statistical study, this is the entire group of individuals about which we want information.

Random assignment

An important experimental design principle. Use some chance process to assign experimental units to treatments. This helps create roughly equivalent groups of experimental units at the start of the experiment.

Random sampling

The use of chance to select a sample; is the central principle of statistical sampling.

Replication

An important experimental design principle. 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.

Response bias

A systemic pattern of incorrect responses.

Response variable

A variable that measures an outcome of a study.

Sample

The part of the population from which we actually collect information. We use information from this to draw conclusions about the entire population.

Simple random sample (SRS)

The basic random sampling method. This method gives every possible sample of a given size the same chance to be chosen. We often choose the sample by labeling the members of the population and using random digits to select the sample. Common ways to choose this type of sample includes drawing names out of a hat, technology random number generators or using tables of random digits.

Statistically significant

An observed effect so large that it would rarely occur by chance.

Strata

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

Stratified random sample

To select a this type of sample, first classify the population into groups of similar individuals, called strata. Then choose a separate SRS from each stratum to form the full sample.

Subjects

Experimental units that are human beings.

Table of random digits

A long string of the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 with these properties:

• Each entry in the table is equally likely to be any of the 10 digits 0 through 9.

• The entries are independent of each other. That is, knowledge of one part of the table gives no information about any other part.

Treatment

A specific condition applied to the individuals in an experiment. If an experiment has several explanatory variables, a treatment is a combination of specific values of these variables.

Undercoverage

Occurs when some members of the population are left out of the sampling frame; a type of sampling error.

Voluntary response samples

People decide whether to join a sample based on an open invitation; particularly prone to large bias.

Wording of questions

The most important influence on the answers given to a survey. Confusing or leading questions can introduce strong bias, and changes in wording can greatly change a survey's outcome. Even the order in which questions are asked matters.