STRATEGIES OF RESEARCH DESIGNthe link between cigarette smoking and lung cancer,
scientists do not say that we have absolute proof.
Instead we can say that overwhelming evidence, or
all studies to date, support or are consistent with
the hypothesis. Scientists never want to close off
the possibility of discovering new evidence that
might contradict past findings. They do not want to
cut off future inquiry or stop exploring intervening
mechanisms. History contains many examples of
relationships that people once thought to be proved
but were later found to be in error. We can use proof
when referring to logical or mathematical relations,
as in a mathematical proof, but not for empirical
research.
Testing and Refining a Hypothesis.Knowledge
rarely advances on the basis of one test of a single
hypothesis. In fact, researchers can get a distorted
picture of the research process by focusing on a single
study that tests one hypothesis. Knowledge develops
over time as many researchers across the scientific
community test many hypotheses. It slowly grows
from shifting and winnowing through many hypothe-
ses. Each hypothesis represents an explanation of a
dependent variable. If the evidence fails to support
some hypotheses, they are gradually eliminated from
consideration. Those that receive support remain in
contention. Theorists and researchers constantly cre-
ate new hypotheses to challenge those that have
received support (see Figure 3). From Figure 3 we
see that in 2010, three hypotheses are in contention,
but from 1970 to 2010, eleven hypotheses were con-
sidered, and over time, eight of them were rejected
in one or more tests.
Scientists are a skeptical group. Supporting a
hypothesis in one study is not sufficient for them to
accept it. The principle of replication says that a
hypothesis needs several tests with consistent and
repeated support before it can gain broad accept-
ance. Another way to strengthen confidence in a
hypothesis is to test related causal linkages in the
theory from which it comes.
As scientists, we accept the strongest contender
with the greatest empirical support as the best expla-
nation at the time. The more alternatives we test a
hypothesis against, the more confidence we have
in it. Some tests are called crucial experimentsor
crucial studies. This is a type of study wherebytwo or more alternative explanations for some phe-
nomenon are available, each being compatible with
the empirically given data; the crucial experiment
is designed to yield results that can be accounted
for by only one of the alternatives, which is thereby
shown to be “the correct explanation.” (Kaplan,
1964:151–152)Thus, the infrequent crucial experiment is an impor-
tant test of theory. Hypotheses from two different
theories confront each other in crucial experiments,
and one is knocked out of the competition. It is rare,
but significant, when it occurs.Types of Hypotheses.Hypotheses are links in
a theoretical causal chain and are used to test the
direction and strength of a relationship between vari-
ables. When a hypothesis defeats its competitors,
it supports the researcher’s explanation. A curious
aspect of hypothesis testing is that researchers treatEXAMPLE BOX 4
Ways to State Casual RelationsReligious attendance causesreduced divorce.
Religious attendance leads toreduced divorce.
Religious attendance is related toreduced divorce.
Religious attendance influencesthe reduction of
divorce.
Religious attendance is associated withreduced
divorce.
Religious attendance producesreduced divorce.
Religious attendance results inreduced divorce.
Ifpeople attend religious services, thenthe likelihood
of divorce will be reduced.
The higherreligious attendance, the lowerthe like-
lihood of divorce.
Religious attendance reduces the likelihood of
divorce.Crucial experiment A direct comparison and eval-
uation of competing explanations of the same
phenomenon designed to show that one is supe-
rior to the other.