Chapter 3: Explanations, Hypotheses,
and Making Comparisons
Preliminaries
 In previous lectures you learned that political science research starts with defining and
measuring concepts.
 Measurement entails:
 Defining the concept to be measured clearly.
 Accurate measurement of the concept.
 Selecting variables or indices to accomplish that measurement.
 The measurement process is intended to identify clearly what it is you want to study, and
then obtain empirical data which represents that concept.
 However, the process does not stop here.
 We need to propose and test explanations for the political phenomenon we want to
study.
 Here the concern is over “why” relationships might exist among our research concepts.
Elements of Explanations
 Any explanation for research concepts entails explaining variation and covariation.
 If a concept y varies, why does it vary?
 Does y covary with another concept x?
 As political scientists, we seek to understand differences, variations, and covariations?
 Examples:
 Why do people in the United States turnout/not turnout to vote?
 Country 1 has more democratic institutions than country 2. Why?
 Some people are opposed to “abortion on demand?” Why?
 Some states place more restrictions on abortion than others. Why?
 Some people turn out to vote, while others do not. Why?
 Public liberalism and conservatism can be shown to vary through time. Why?
 Presidential approval ratings rise and fall through time. Why?
 Some people think it would be a good idea for college students to be able to carry concealed
weapons on college campuses. Others do not. What explains these differences?
 Good explanations describe a connection between a dependent variable and a causal
variable. A causal variable is also called an independent variable.
 Example:
 Support for concealed weapons on college campuses is a function of people’s
partisanship.
 Good explanations provide a direction for relationships.
 Example:
 Support for concealed weapons on college campuses is higher among Republicans
than it is among Democrats.

Good explanations should also be testable.
 Example:
 Do an opinion survey among the general population. Construct a measure of support
for concealed weapons on college campuses. Record the respondents’ partisanship
during the survey. We should find covariation in the expected direction if the
explanation is true.
 Is this explanation exhaustive? Are there some other reasons people might support or not
support concealed weapons on college campuses.
Hypotheses
 An hypothesis is a testable statement about the empirical relationship between an
independent variable and a dependent variable.
 An hypothesis tells us how different values of a dependent variable should be related to
values of an independent variable.
 Examples:
 Explanation: Support for gun regulation is a function of partisanship.
 Hypothesis: Support for concealed weapons on college campuses should be higher
among Republicans than among Democrats.
 Explanation: Voter turnout is a function of voter demographics
 Hypothesis: Voter turnout should be higher among older people than it is among
younger people.
 Hypothesis: Voter turnout should be higher among better educated people than
among lower educated people.
 Hypothesis: Voter turnout should be higher among people with high incomes than
among people with low incomes.
 Why do some people favor candidates or policies, while others disfavor certain
candidates or policies? Competing theories.
 Rationality - People favor policies and/or candidates that promote their own personal
self-interest.
 Hypothesis: Voting Republican should be greater among those with higher income.
 Hypothesis: Voting for the incumbent candidate should depend on the individual’s
personal financial situation in the recent past.
 Hypothesis: Non-support for efforts to slow global climate change should be greater
among those who work in industries which pollute the environment.
 Sociotropic - People favor policies or candidates that maximize “social welfare”.
 Hypothesis: Support for environmental regulation should be greater among those
whose values are communitarian, rather than individualistic.
 Hypothesis: People who view the economy as a whole as performing well, regardless
of their own financial situation, are more likely to vote for the incumbent candidate.
 Hypothesis: Cross-nationally, countries having values more supportive of equity
should be more supportive of programs to help the poor.
Testing Hypotheses with Descriptive Statistics or
Comparisons
 We can easily use the tools you have learned up to now to construct some basic tests of
hypotheses.
 However, note that these are very basic tests which do not provide measures of certainty
about the hypotheses.
 Examples:
Hypothesis: Smoking is a function of one’s income level (a proxy for health
sophistication).
Hypothesis: A higher level of economic development produces greater support for
civil liberties. (Or, does the relation run in the other direction?)
Hypothesis: Students who study more perform better in their courses.
Hypothesis: Voter turnout is higher among older people than it is
among younger people.
Hypothesis: Political Activists are more likely to turnout to vote.
Hypothesis: Collective bargaining bolsters economic welfare for the middle class.
Hypothesis: Support for gun control is higher among Democrats than among
Republicans.
Hypothesis: Smoking is higher among low income groups (a proxy for health
sophistication).
Hypothesis: A higher level of economic development produces greater support
for civil liberties. (Or, does the relation run in the other direction?)
Hypothesis: Collective bargaining bolsters economic welfare for the middle class.
Same as before using group percentages, rather than a graph.