Statistics Chapter 4

What is a block?

A block is 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.

What is a lurking variable?

A lurking variable is a variable that is not among the explanatory or response variables in a study but that may influence the response variable.

What is a matched-pairs design?

A matched-pairs design is a randomized blocked experiment in which each block consists of a matching pair of similar experimental units. Chance is used to determine which unit in each pair gets each treatment. Sometimes, a "pair" in a matched-pairs design consists of a single unit that receives both treatments. Since the order of the treatments can influence the response, chance is used to determine with treatment is applied first for each unit.

What is a sample?

A sample is the part of the population from which we actually collect information. We use information from a sample to draw conclusions about the entire population.

What is a simple random sample (SRS)?

A 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.

What is a treatment?

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

What is a voluntary response sample?

A voluntary response sample consists of people who choose themselves by responding to a general appeal. Voluntary response samples show bias because people with strong opinions (often in the same direction) are most likely to respond.

What is a stratified random sample?

An SRS involves sampling important groups (called strata) within the population separately. These "sub- samples" are combined to form one stratified random sample.

What is an experiment?

An experiment deliberately imposes some treatment on individuals to measure their responses.

What is an observational study?

An observational study observes individuals and measures variables of interest but does not attempt to influence the responses.

What does "statistically significant" mean?

An observed effect so large that it would rarely occur by chance is called statistically significant. *A statistically significant association in data from a well-designed experiment does imply causation.*

What is a convenience sample?

Choosing individuals who are easiest to reach results in a convenience sample.

What is confounding?

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

What are the three principles of experimental design?

Control: for lurking variables that might affect the response. Random assignment: use impersonal chance to assign experimental units to treatments. Replication: Use enough experimental units in each group so that any differences int he effects of the treatments can be distinguished from chance differences between the groups.

What are three non-sampling errors?

Nonresponse, response bias, and wording of questions

What are two types of sampling errors?

Random sampling error is theerror that arises as a result of taking a sample from a population rather than using the whole population. Undercoverage is a type of selection bias. It occurs when some members of the population are inadequately represented in the sample. (A classic example of undercoverage is the Literary Digest voter survey, which predicted that Alfred Landon would beat Franklin Roosevelt in the 1936 presidential election. The survey sample suffered from undercoverage of low-income voters, who tended to be Democrats. )

What is random sampling?

Random sampling, the use of chance to select a sample, is the central principle of statistical sampling.

How do studies show bias?

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

What are experimental units?

The experimental units are the smallest collection of individuals to which treatments are applied. When the units are human beings, they often are called subjects.

What is a population?

The population in a statistical study is the entire group of individuals about which we want information.

What is inference?

The process of drawing conclusions about a population on the basis of sample data is called inference.

If the individuals were randomly selected, what inferences can we make?

If the individuals were randomly assigned to groups, we can make an inference about the population and about cause and effect. If the individuals were NOT randomly assigned to groups, we can make an inference about the population but NOT about cause and effect.

If the individuals were randomly assigned, what inferences can we make?

If the individuals were randomly selected, we can make an inference about cause and effect but NOT about cause and effect. If the individuals were NOT selected, we CANNOT make an inference about the population and CANNOT make an inference about cause and effect.

What is a completely randomized design?

In a completely randomized design, the treatments are assigned to all the experimental units completely by chance.

What is a randomized block design?

In a randomized block design, the random assignment of experimental units to treatments is carried out separately within each block.

What is random assignment?

In an experiment, random assignment means that experimental units are assigned to treatments at random, that is, using some sort of chance process.

How do you select a stratified random sample?

To select a stratified random sample, first classify the population into groups of similar individuals, called strata. Then choose a separate SRS in each stratum and combine these SRSs to form the full sample.

How do you take a cluster sample?

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