Stats Chap. 1

Data

Collections of observations such as measurements, genders, or survey responses.

Statistics

The science of planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, and interpreting data and then drawing conclusions based on them.

Population

The complete collection of all measurements or data that are being considered.

Census

The collection of data from every member of the population.

Sample

A sub-collection of members selected from a population.

Voluntary Response Sample

A sample in which the respondents themselves decide whether or not to be included.

Statistical Significance

Achieved in a study when we get a result that is very unlikely to occur by chance.

Correlation

Association between two variables.

Nonresponse

Occurs when someone either refuses to respond to a survey question or is unavailable.

Parameter

Numerical measurement describing some characteristic of a population.

Statistic

Numerical measurement describing some characteristic of a sample.

Quantitative/Numerical Data

Consist of numbers representing counts or measurements.
i.e.: The age of survey respondents

Categorical/Qualitative Data

Consist of names or labels that are not numbers representing counts or measurements.
i.e.: One's political affiliation

Discrete Data

Occur when the data values are quantitative and the number of values is finite or countable.

Continuous Data

Result from infinitely many possible quantitative values, where the collection of values is not countable.

Nominal Level of Measurement

Characterized by data that consists of names, labels, or categories only. Cannot be arranged in an ordering scheme.
i.e.: Responses of yes/no/undecided

Ordinal Level of Measurement

Data that can be arranged in some order, but differences between data values cannot be determined or are meaningless.
i.e.: Course Grades

Interval Level of Measurement

Data that can be arranged in order, and differences between values can be found and are meaningful. Do not have a natural zero starting point where none of the quantity is present.
i.e.: Temperatures

Ratio Level of Measurement

Data that can be arranged in order, differences can be found and are meaningful, and there is a natural zero starting point. Differences and ratios are both meaningful.
i.e.: Class times

Observational Study

In an observational study, we observe and measure specific characteristics, but we don't attempt to modify the subjects being studied.

Experiment

In an experiment, we apply some treatment and then proceed to observe its effects on the subjects.

Simple Random Sample

Selected in such a way that every possible sample of the same size n has the same chance of being chosen.

Random Sampling

Each member of the population ha an equal chance of being selected.

Systematic Sampling

Select some starting point, then select every kth element in the population.

Convenience Sampling

Use results that are easy to get.

Stratified Sampling

Subdivide the population into at least two different subgroups so that the subjects within the same subgroup share the same characteristics, then draw a sample from each.

Cluster Sampling

Divide the population into sections, then randomly select some of those clusters, and choose all of their members.

Cross-sectional Study

Data are observed, measured, and collected at one point in time, not over a period of time.

Retrospective Study

Data are collected from the past.

Prospective Study

Data are collected in the future from groups that share common factors.

Cofounding

Occurs in an experiment when the investigators are not able to distinguish among the effects of different factors.

Sampling Error

Occurs when the sample has been selected with a random method, but there is a discrepancy between a sample result and the true population result; such an error results from chance sample fluctuations.

Nonsampling Error

The result of human error.

Nonrandom Sampling Error

The result of using a sampling method that is not random.