1.1_-_1.2_Stats_Reading

Descriptive Statistics

The collection, organization, summarization, and presentation of data.

Inferential Statistics

Generalizing from samples to populations, performing estimations and hypothesis tests.

Variable

A characteristic or attribute that can assume different values.

Data

The values (measurements or observations) that the variables can assume.

Random Variable

A variable whose values are determined by chance.

Population

All subjects (human or otherwise) that are being studied.

Sample

A group of subjects selected from a population.

Census

Data collected from every subject in the population.

Bias in Sampling

Information from a sample is biased if it does not represent the population from which it has been selected.

Qualitative Variable

Variables that have distinct categories according to some characteristic or attribute.

Quantitative Variable

Variables that can be counted or measured.

Discrete Variable

Variables that can be counted; can only take on specific values.

Continuous Variable

Variables that can assume an infinite number of values in an interval between any two specific values.

Nominal Level of Measurement

Classifies data into mutually exclusive categories with no order or ranking.

Ordinal Level of Measurement

Classifies data into categories that can be ranked, but precise differences do not exist.

Interval Level of Measurement

Ranks data and allows for precise differences between units; lacks a true zero.

Ratio Level of Measurement

Has all properties of interval measurement, including a true zero and meaningful ratios between values.

Hypothesis Testing

A decision-making process for evaluating claims about a population based on information obtained from samples.

Statistical Sample

A subset of a population used to estimate characteristics of the whole population.

Apportionment

The process of determining the distribution of seats in a legislative body, such as the House of Representatives.