Identify the population: A survey of 500 adults in the U.S. ofund that 54% drink

Question

Identify the population: A survey of 500 adults in the U.S. ofund that 54% drink coffee daily. Collection of the 500 adults surveyed Collection of all adults in the U.S. 54% 500 None Identify the sample: A survey of 500 adults in the U.S. ofund that 54% drink coffee daily. Collection of the 500 adults surveyed Collection of all adults in the U.S. 54% 500 None Identify the data set's level of measurement: The IQ scores of students in a class. Nominal Ordinal Interval Ratio None Identify the data set's level of measurement: The nationality of each person on an airplane. Nominal Ordinal Interval Ratio None Identify the data set's level of measurement: The salaries of nurses at a hospital. Nominal Ordinal Interval Ratio None

Explanation / Answer

1) B. Collection of all adults in the U.S.

2) A. Collection of the 500 adults surveyed

3) C. Interval

4) A.Nominal

5) D.Ratio

There are four levels of data measurement. Ranked from top to bottom in order of complexity and information content these are:

Each level of measurement is characterized by its properties. Nominal measurement has just one property:CLASSIFICATION. Ordinal measurement has two properties: CLASSIFICATION and ORDER. Interval measurement has three properties: CLASSIFICATION, ORDER and EQUAL INTERVALS. Ratio data has four properties: CLASSIFICATION, ORDER, EQUAL INTERVALS and TRUE ZERO. Because the higher levels of measurement contain more properties and more information, they permit a wider variety of interpretations.

Nominal Data

Properties: classification
Observations reflect: differences in kind
Examples: gender, ethnic background, political affiliation, handedness, major in college

Ordinal Data

Properties: classification, order
Observations reflect: differences in degree
Examples: Likert scale categories, rankings, academic letter grade, stages in development

Interval Data

Properties: classification, order, equal intervals
Observations reflect: measurable differences in amount
Examples: IQ scores, degrees of temperature, magnitude estimation scales

Ratio Data

Properties: classification, order, equal intervals, true zero
Observations reflect: measurable differences in total amount
Examples: weight, income, family size, number of cows in a field

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