Social Research Methods: Qualitative and Quantitative Approaches

QUALITATIVE AND QUANTITATIVE MEASUREMENT

is a dependable, stable, and responsible person who
responds in similar, predictable ways in different
times and conditions. A reliablecar is dependable
and trustworthy; it starts and peforms in a predica-
ble way. Sometimes, we say that a study or its results
are reliable. This means that other researchers can
reproduce the study and will get similar results.
Internal validitymeans we have not made errors
internal to the design of a research project that might
produce false conclusions.^13 In experimental re-
search, we primarily talk about possible alternative
causes of results that arise despite our attempts to
institute controls.
External validityis also used primarily in
experimental research. It refers to whether we can
generalize a result that we found in a specific setting
with a particular small group beyond that situation
or externally to a wider range of settings and many
different people. External validity addresses this
question: If something happens in a laboratory or
among a particular set of research participants (e.g.,
college students), does it also happen in the “real”
(nonlaboratory) world or among the general popu-
lation (nonstudents)? External validity has serioius
implications for evaluating theory. If a general the-
ory is true, it implies that we can generalize find-
ings from a single test of the theory to many other
situations and populations (see Lucas, 2003).
Statistical validitymeans that we used the
proper statistical procedure for a particular purpose

and have met the procedure’s mathematical re-

quirements. This validity arises because different

statistical tests or procedures are appropriate for

different situations as is discussed in textbooks on

statistical procedures. All statistical procedures rest

on assumptions about the mathematical properties

of the numbers being used. A statistic will yield

nonsense results if we use it for inappropriate situ-

ations or seriously violate its assumptions even if

the computation of the numbers is correct. This is

why we must know the purposes for which a statis-

tical procedure is designed and its assumptions to

use it. This is also why computers can do correct

computations but produce output that is nonsense.

A GUIDE TO QUANTITATIVE

MEASUREMENT

Thus far, we have discussed principles of measure-

ment. Quantitative researchers have specialized

measures that assist in the process of creating oper-

ational definitions for reliable and valid measures.

This section of the chapter is a brief guide to these

ideas and a few of the specific measures.

Levels of Measurement

We can array possible measures on a continuum. At

one end are at “higher” ones. These measures con-

tain a great amount of highly specific information

with many exact and refined distinctions. At the

A Bull’s-Eye = A Perfect Measure

Low Reliability

and Low Validity

High Reliability

but Low Validity

High Reliability

and High Validity

FIGURE 6 Illustration of Relationship between Reliability and Validity

Source:Adapted version of Figure 5-2 An Analogy to Validity and Reliability, page 155 from Babbie, E. R. 1986. The Practice of
Social Research, Fourth Edition. Belmont, CA: Wadsworth Publishing Company.