Steps in Formulating a
Hypothesis
-
- Decide what you want to
explain: choose a dependent variable
- Your dependent
variable must show variation
- Run
Descriptives to see mean and dispersion
statistics
- Even better, run
Frequencies, and call for a histogram
along with the mean and std. dev (suppress the
Frequency table itself)
- Choose
independent variables that also show
variation
- One can't explain
variation in a dependent variable with an independent
variable that doesn't vary.
- Moreover, the
variation in the independent must match that in
the dependent variable.
- Otherwise, they can't
possibly covary, which is needed for the
covariation needed in correlation.
- Examples
of lack of theoretical potential:
- Voting for Clinton
in 1996 in the suburb of Winnetka can't be
explained by race, for race does not vary much in
Winnetka.
- Variation across
time in deaths in domestic violence within
nations can't be explained by ethnic diversity, for
ethnicity doesn't change much across time within a
nation.
- However, variation
in deaths across nations can be
related to variation in ethnic diversity across
nations.
- Think of multiple
causes of the dependent variable:
- Do two or more
independent variables combine to affect it?
- Consider using
multiple regression to deal with
multiple causes.
- Does a relationship
hold for some units of analysis but not others?
- For northern
states but not for southern ones?
- For European
nations but not for Third World
nations?
- For whites, but
not for blacks?
- For reformed
cities, but not unreformed cities?
- For multi-party
states, but not single-party states?
- Try to develop your
analysis so that it considers all the cases,
even if the relationship doesn't apply equally to
them.
- Consider alternative
measures of both the dependent and independent
variables.
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