Statistics Fundamentals and Data Biases

A set of vocabulary flashcards covering basic statistical terms, data classification levels, and sources of statistical bias or misrepresentation.

Population

The complete collection of all elements being studied.

Census

Data collected from every member of a population.

Sample

A smaller group selected from a population.

Parameter

A numerical measurement describing a population.

Statistic

A numerical measurement describing a sample.

Quantitative Data

Numerical data.

Qualitative Data

Categorical or descriptive data.

Discrete Data

Countable numerical data, usually whole numbers with gaps.

Continuous Data

Numerical measurements that can take any value within a range, including decimals.

Nominal

Data placed into categories or labels with no order.

Ordinal

Data that can be ranked or ordered, but differences between values aren't meaningful.

Interval

Ordered numerical data where differences are meaningful, but there is no true zero.

Ratio

Ordered numerical data with meaningful differences and a true zero.

Intentionally Deceptive

Statistics presented in a way that purposely misleads people.

Extrapolation

Using existing or past data to predict what will happen beyond the data.

Small Sample

Using too few people/data points to accurately represent a population.

Partial Picture

Showing only part of the available data or time period, which can create a misleading conclusion.

Loaded Questions

Questions worded in a way that pushes someone toward a particular answer.

Misleading Graphs

Graphs designed or scaled in a way that makes the data appear different from what it really is.

Pollster Pressure

When the person asking questions influences or pressures someone toward a certain response.

Self-Selected Bias

Bias caused when people choose themselves to participate, meaning the group may not represent everyone.

Incompetence

Errors caused by incorrect math, calculations, or handling of data.