Which type of data take on names or labels (such as color or gender) and cannot be averaged?

Which type of data take on names or labels (such as color or gender) and cannot be averaged?

• A. Categorical variables
• B. Measured variables
• C. Construct validity
• D. Sampling frame

Answer: (A)

Data that take on names or labels are categorical (nominal) data. These are qualitative categories such as color or gender, and there is no inherent numeric meaning or order to the labels. Because the values aren’t numbers with a real distance between them, calculating an average isn’t meaningful. Instead, you summarize these data by counting how many observations fall into each category and by reporting proportions or percentages; the most common category is the mode. Measured variables, by contrast, are numerical and can be averaged because their values have meaningful quantities and intervals. Construct validity is about whether a test measures the intended construct, not about the type of data. A sampling frame is the list or source from which participants are drawn, again not a data type.

Data that take on names or labels are categorical (nominal) data. These are qualitative categories such as color or gender, and there is no inherent numeric meaning or order to the labels. Because the values aren’t numbers with a real distance between them, calculating an average isn’t meaningful. Instead, you summarize these data by counting how many observations fall into each category and by reporting proportions or percentages; the most common category is the mode.

Measured variables, by contrast, are numerical and can be averaged because their values have meaningful quantities and intervals. Construct validity is about whether a test measures the intended construct, not about the type of data. A sampling frame is the list or source from which participants are drawn, again not a data type.