This page focuses on the sources of data collection and the importance of controlling external factors in statistical research.

Definition: Extraneous variables are additional factors that could affect experimental results but are not the focus of the study.

Highlight: Primary data is collected firsthand through methods like questionnaires, interviews, experiments, and observations, while secondary data comes from existing sources like newspapers, databases, and government statistics.

The page compares the advantages and disadvantages of different data sources:

Example: Primary data advantages include direct relevance to hypothesis and known reliability, while disadvantages include time and cost constraints.

Quote: "Secondary data is quick, easy to find, and cheap, with access to larger data sets than individual collection might allow."

Vocabulary: The Office for National Statistics (ONS) is referenced as a government source for secondary data collection.

This page introduces fundamental concepts of data classification and measurement scales in statistics. The content explores various ways data can be categorized and measured for statistical analysis.

Definition: Raw data refers to unprocessed, newly collected information that requires ordering, grouping, rounding, or cleaning before analysis.

Vocabulary: Qualitative data represents non-numerical information, while quantitative data consists of numerical values that can be either continuous or discrete.

Example: Discrete data might include shoe sizes or number of people, while continuous data includes measurements like height, weight, or time.

The page elaborates on different data scales and variable types:

Highlight: Data can be classified as univariate (single variable), bivariate (two variables), or multivariate (three or more variables).

Definition: Variables are classified as explanatory (independent) variables on the x-axis or response (dependent) variables on the y-axis, representing the relationship between what is controlled and what is measured.