A method of data collection

A type of measurement scale

A specific value in a data set

A characteristic that can assume different values

Descriptive statistics summarizes data, while inferential statistics determines relationships among variables

Descriptive statistics collects data, while inferential statistics makes predictions

Descriptive statistics generalizes from samples to populations, while inferential statistics organizes data

Descriptive statistics uses probability, while inferential statistics represents data visually

Weight

Number of children in a family

Height

Temperature

Nominal

Ordinal

Ratio

Interval

Cross-sectional study collects data over a period of time, while retrospective study collects data at one time

Cross-sectional study collects data using records obtained from the past, while retrospective study collects data from every subject in the population

Cross-sectional study observes what has happened in the past, while retrospective study observes what is happening

Cross-sectional study tries to draw conclusions based on observations, while retrospective study manipulates variables

The dependent variable

The resultant variable

The treatment group

The manipulated variable

An effect on an outcome variable caused by the difference between sample and population results

An effect on an outcome variable caused by nonsampling errors

An effect on an outcome variable caused by the manipulation of variables

An effect on an outcome variable caused by the fact that subjects know they are participating in the study

A variable that influences the dependent variable but was not separated from the independent variable

A variable that is manipulated in an experimental study

A variable that is measured on two different members of the population

A variable that is classified into mutually exclusive categories

A method of selecting a sample by measuring every 10th bottle

A method of selecting a sample based on convenience or availability

A method of selecting a sample using random numbers

A method of selecting a sample by dividing a group and randomly selecting from each group

An error that occurs when the data are obtained erroneously or the sample is biased

An error that influences the dependent variable but was not separated from the independent variable

An error caused by the fact that subjects know they are participating in the study

The difference between the results obtained from a sample and the results obtained from the population