In Exercises 11 and 12, determine whether the data are qualitative or quantitative, and determine the level of measurement of the data set.


The six top-earning states in 2019 by median household income are listed. (Source: U.S. Census Bureau)
1. Maryland 2. New Jersey 3. Hawaii
4. Massachusetts 5. Connecticut 6. Alaska

Verified step by step guidance

1. Step 1: Understand the difference between qualitative and quantitative data. Qualitative data describes categories or qualities (e.g., names, labels), while quantitative data represents numerical values that can be measured or counted.
2. Step 2: Analyze the given data. The data consists of the names of the six top-earning states by median household income. These are categorical labels and do not represent numerical values, so the data is qualitative.
3. Step 3: Understand the levels of measurement. The four levels of measurement are nominal, ordinal, interval, and ratio. Nominal data consists of names or labels without any inherent order, while ordinal data has a meaningful order or ranking.
4. Step 4: Determine the level of measurement for the data. Since the states are listed in a ranked order based on their median household income, the data is ordinal. The ranking implies a meaningful order, but the differences between ranks are not numerically measurable.
5. Step 5: Conclude that the data is qualitative and has an ordinal level of measurement because it represents ranked categories (states) based on a specific criterion (median household income).

Key Concepts

Qualitative vs. Quantitative Data

Qualitative data refers to non-numerical information that describes characteristics or qualities, such as names or categories. In contrast, quantitative data consists of numerical values that can be measured or counted, allowing for statistical analysis. Understanding the distinction between these two types of data is crucial for determining how to analyze and interpret the information presented.

Levels of Measurement

The levels of measurement categorize data based on the nature of the information they represent. There are four levels: nominal (categorical data without order), ordinal (categorical data with a defined order), interval (numerical data without a true zero), and ratio (numerical data with a true zero). Identifying the correct level of measurement is essential for selecting appropriate statistical methods and accurately interpreting results.

Median Household Income

Median household income is a measure that represents the middle income value of a dataset, where half of the households earn more and half earn less. It is a key indicator of economic health and is often used to compare income levels across different regions. Understanding this concept helps in analyzing the socioeconomic status of the states listed in the question.