Statistics

The second step of the statistical process: design a _ to answer the question

The third step of the statistical process: collect _

The fourth step of the statistical process: exploratory _, or "initial look" at data, with graphs and _

The fifth step of the statistical process: _ analysis of the data, i.e. _ testing

The sixth step of the statistical process: answer the _ of interest

Rows in a data table typically represent individual "_" about which characteristics are recorded

People in a survey are called _

The subjects of an experiment are called _

Rows in a database are called _

The characteristics recorded about each individual are called _

A variable that names categories & answers questions about how cases fall into categories is called a _ variable

A measured variable with units that answers questions about the quantity of what is measured is called a _ variable

A variable that reports order without natural units is called a _ variable

_ variables act as labels & allow combination of data from different sources

A _ variable is quantitative, and its units are integers

A _ variable is quantitative, and its units can be integers or fractions

Computers generate "_" numbers in a fixed sequence, but it appears random because only a _number of values can be represented

A pseudorandom sequence of numbers will eventually _ itself

Studies have shown that a deck of cards should be shuffled at least _ times for best randomness

Each time an answer is obtained in an experiment, it is called a _

The method of selecting certain individuals from a population of interest to participate in a study

Sampling is used when limited _ make it impossible to collect data on the entire population

If sampling is done properly, _ can be drawn about the entire population based on data collected from the sample.

The main goal of sampling is to draw a sample from the population such that the sample is _ of the population

Sampling is ideally performed as _ as possible

A systematic error that favors one outcome over another; can over- or under-_ any effects on the population

A type of bias in which some people are not included in the selection

A type of bias in which individuals chosen for the study can't or won't participate

A type of bias in which the individual doesn't respond accurately or honestly for some reason

A sample design in which every Kth individual is chosen; use a random number generator to select the "starting point"

A sample design in which individuals are first divided into groups of similar individuals, then random sampling within each one

A sample design in which random samples are subdivided into "clusters", some of which are randomly selected, and fully sampled