Your nationality, city that you live in, model of your car(s), colour of your eyes.
Variables measured in monetary units
Nominal variables are categories without a natural order or ranking. Examples include gender (male, female, non-binary), marital status (single, married, divorced), and types of cuisine (Italian, Chinese, Mexican). These variables are used to label or classify data and can be analyzed using frequency counts or mode. They do not possess numerical value or quantifiable differences.
The appropriate measure of dispersion for nominal variables is the mode, as it identifies the most frequently occurring category within the dataset. Since nominal variables represent distinct categories without a meaningful order, other measures of dispersion, such as range or standard deviation, are not applicable. In addition to the mode, frequency distribution can also provide insights into the distribution of nominal data.
A nominal variable is a type of categorical variable that represents distinct categories without any inherent order or ranking. Examples include gender, nationality, or favorite color, where the values serve to label different groups. Since nominal variables do not have a quantitative value, statistical analysis typically involves counting occurrences or determining proportions within each category.
Nominal numbers are always discrete.An example would be personality types. You can't have a half or a fourth of a defined personality.
Variables measured in monetary units
Nominal and ordinal variables are both qualitative or discrete variables. Nominal variables allow for only qualitative classification while an ordinal variable is a nominal variable, but its different states are ordered in a meaningful sequence.
Examples of nominal accounts are losses and expenses of gains or income.
Nominal Variables
The appropriate measure of dispersion for nominal variables is the mode, as it identifies the most frequently occurring category within the dataset. Since nominal variables represent distinct categories without a meaningful order, other measures of dispersion, such as range or standard deviation, are not applicable. In addition to the mode, frequency distribution can also provide insights into the distribution of nominal data.
There are many ways of categorising variables. One classification, used in statistics, is Nominal, Ordinal and Interval.
nominal and ordinal is wrong; those are the two types of qualitative variables. Ratio and interval are the two types of quantitative variables.
Nominal level of measurement is defined as the level of measurement that classifies variables by assigning names or categories that are mutually exclusive and exhaustive. It was often called qualitative scales, and measurements made on qualitative scales were called qualitative data. Examples are gender, nationality, ethnicity, language, genre, style, biological species, and form.
A nominal number names something-a telephone number, a player on a team. Nominal numbers do not show quantity or rank. They are used only to identify something.Here are some examples using nominal numbers:jersey number 4zip code 02116
Nominal numbers are always discrete.An example would be personality types. You can't have a half or a fourth of a defined personality.
Labour is a variable,Population,Stock etc are variables
Examples of code will be shown. match it to the correct vocabulary. Variables are represented by ()