Question

Label the type of each variable listed in the dataset as either quantitative or categorical, and denote its scale of measurement (ratio, interval, ordinal, nominal).

• Wage (average hourly earnings)
• Education (years of education)
• Experience (years of experience)
• Tenure (length of time employed)
• Race
• Gender
• Married
• Dependents

Answer 1

Wage (Average hourly earnings) :

This is a quantitative variable because it has numbers or its numerical .

Its scale of measurement is ratio , as even 0 wage has a meaning.

Education (years of education):

This is a quantitative variable because it has numbers or its numerical.

Its scale of measurement is ratio, as even 0 years of education has a meaning.

Experience (years of experience):

This is a quantitative variable because it has numbers or its numerical.

Its scale of measurement is ratio, as even 0 years of experience has a meaning.

Tenure (length of time employed):

This is a quantitative variable because it has numbers or its numerical.

Its scale of measurement is ratio, as even 0 tenure (length of time employed) has a meaning.

Race :

This is a categorical variable because its related to a characteristic of a person.

Its scale of measurement is nominal, as the label it represent has no quantitative value , and only used to label data.

Gender:

This is a categorical variable because its related to a characteristic of a person.

Its scale of measurement is nominal, as the label it represent has no quantitative value , and only used to label data.

Married:

This is a categorical variable because its related to a characteristic of a person.

Its scale of measurement is nominal, as the label it represent has no quantitative value , and only used to label data.

Dependents:

This is a quantitative variable because it has numbers or its numerical .

Its scale of measurement is discrete, as its values are distinct. This type of data can be counted but can't be measured.