Data chapter 3

Categorical data

Data that is represented by words—such as grouping a collection of people by gender (e.g., male, female, nonbinary) or categorizing transaction types (sales vs. returns).

numerical data

Data represented by meaningful numbers, such as transaction amount, age, or the score on an exam.

nominal data

Categorical data that cannot be ranked. Examples include transaction type (purchase, return).

The two primary method to summarize categorical, nominal data

Counting and grouping and proportion

proportion

The number of observations in one category; that number is then divided by the grand total number of all available observations

ordinal data

Categorical data with natural, ranked categories (examples include letter grades [e.g., A, B, C, D, and F] and Olympic medals [e.g., gold, silver, bronze]).

Three primary methos to summarize ordinal data

counting and grouping, proportion, and ranking

ranking

A position on a scale.

interval data

Numerical data measured along with a scale. Examples include a thermometer or SAT scores.

four primary methods to summarize numerical data are

Counting and grouping, proportion, Summing, averaging

ratio data

Numerical data with an equal and definitive ratio between each data point; absolute “zero” in ratio data is the point of origin.

data dictionary

A centralized repository of information about data containing a separate record for each field/variable in the database.

audit data standards

A tool developed by the AICPA to provide a consistent framework for organizing and reporting financial data. Functions as a data dictionary.