scopes

what are normative statements

• Evaluative

• Value-laden

• Prescriptive

• Addresses what is good/bad/ought to be

what are empirical/scientific statements

• based on actual objective observation of phenomena to gain scientific knowledge

• Based on empirical verification → studies aren’t theoretical

• Non-normative → doesn't address good/bad; tells it how it is

• Reproducible → findings can be shown over and over again

• Transmissible → research methods = explicit and can be replicated

• General

• Explanatory → explains what things caused this and the variables that account for the differences

• Provisional

what is theory

systematic explanation for observations

what is political theory

broad generalizations bundled together based on a set of axioms or assumptions about a political phenomena; Explains & predicts political phenomena

what is the null hypothesis

• statement indicating that there is no relationship between the variables in a hypothesis

• We test the null hypothesis rather than hypothesis

• Can’t prove causality; focus on disproof rather than proof

• Assumed to be true unless results from research/statistical analysis indicate otherwise

  • Statistical analysis results are used to either reject OR fail to reject null hypothesis

what is the working/alternative hypothesis

• specific, testable statement of a relationship derived from a theory

• Educated guess; inductive observation/presumption based on theory

• States the nature of relationship between 2 or more variables

  • Must have at least 1 independent variable & 1 dependent variable

• Predicts research outcome

what are the qualities of a scientific hypothesis

• An empirical statement → educated assertion about relationships that really exists

  • Not what ought to be true/what the researcher wants to be true

• General → should explain a general phenomenon rather than one occurrence

• Plausible → should be logical to assume the relationship will be confirmed

• Specific → should include negative/positive direction if appropriate & be carefully defined with unit of analysis

• Consistent with data → stated how the researcher intends to test it

• Testable → variables must be measurable & data must be obtainable/able to indicate whether the hypothesis is correct or incorrect

what is a variable

• anything that can produce 2 or more different values when measured

• Must have observable characteristics that can have more than one value

• Must be measurable/able to be operationalized

what are quantitative variables

• reflect a quantity/amount

• Measurement consists of numbers representing value of phenomenon being studied

• Differences between numbers/categories can be expressed numerically

• Ex: age, income, years of education, # of children

what are qualitative variables

• reflect quality/category

• Variables have discrete categories designated by words/labels

• Differences between categories cannot be expressed numerically

• Ex: gender, political party, race

what is the dependent variable/criterion variable

• variable of primary interest in a study

• Hypothesis predicts changes to this variable

• Variable that is influenced/changed by independent variable

what is the independent variable/predictor variable

• manipulation/variation of this variable = hypothesized to affect changes in dependent variable

• Used to explain changes in dependent variable

what is a confounding variable

related to both independent & dependent variables; enhances/hides relationship

what is an intervening variable

• confounding variable that occurs between relationship of independent & dependent variables

• Ex: education & exposure to social diversity affect political tolerance (education = independent, exposure = intervening, political tolerance = dependent)

what is an antecedent variable

• confounding variable that occurs prior to relationship of independent & dependent variables

• Ex: healthcare adequacy affects attitude towards healthcare & support for Obamacare (healthcare adequacy = antecedent, attitude = independent, ACA support = dependent)

how can confounding variables be controlled

by having a large probability sample compared to size of population being studied

what is a correlational relationship

any relationship where the variables perform in a synchronized manner; doesn’t tell us whether one causes another

what is a causal relationship

relationship between 2 variables where changes in 1 variable’s values affect changes in values of the other variable

what is a spurious relationship

• apparent causal relationship between independent & dependant variables that is actually due to one or more other true variables

• Differs from confounding variables → independent variables codependently influencing the dependent variable

• Only superficially appears to be an influence/effect because the true variable is masked by spurious/unrelated variable

what are the criteria for causality

• Correlation → you can have correlation without causality but can’t have causality without correlation

• Time order → cause must proceed effect; independent variable must come before dependent variable

• Non-spurious → real correlation; relationship isn’t a coincidental correlation between 2 variables shown to be caused by a third unrelated variable

what is a positive/direct relationship

• variables vary together in the same direction

• As one variable increases, the other increases

• As one variable decreases, the other decreases

• Ex: newspaper readership & political awareness, education & income, age & conservatism

what is a negative/inverse relationship

• variables vary in opposite direction

• As one variable increases, the other decreases

• Ex: age & tolerance of protest, income & concern for mass transit, GDP & property crime

what is a directional hypothesis

• precise statement explicitly indicating the nature & direction of relationship between the variables

• Used when both the independent & dependent variables = quantitative or have rank order

• Must always state direction (negative/inverse or positive/ direct)

what is a non-directional hypothesis

• only states that a relationship will occur

• Cannot have a directional hypothesis if a nominal variable is included in hypothesis (ex: race, party, political party, religion)

what are the components of a strong hypothesis

• Explicitly states direction of relationship

• States independent variable first, then dependent variable (cause & effect)

• Includes unit of analysis

• Uses one of the values of a dichotomous variable to specify predicted outcome

• Refers to variables by name instead of “independent” & “dependent” variable

what are the components of a strong null hypothesis

• Simple → state there is no relationship between the variables

• Don’t include direction even if it was included in the hypothesis

• State the independent variable first, then dependent variable (cause & effect)

• Include unit of analysis

• Do not use one of the values of a dichotomous variable to specify the relationship

• Refers to variables by name instead of “independent” & “dependent” variable

what is conceptualization

statement of the meaning of a particular concept

what is operationalization

Specification of process a concept/variable is measured by; leads to an operational definition of the concept

what are values

• observation we choose to consider as a reflection of measurement for a variable

• Ex: male/female = values of gender

what is an indicator

• Measurement tool such as a question on a survey, scale of values to measure the phenomenon

• each variable in a study requires at least one indicator

• Complex variables may require multiple indicators to be aggregated into a total measure to arrive at true/valid measurement of phenomenon

what is a unit of analysis

• entity about whom/which the researcher gathers info to compare

• what/whom is being analyzed

• Individual data → based on single entity rather than collections of entities

  • Ex: an individual person responding to a survey

• Aggregate data → based on groups/units put together

  • Ex: census, organizations, agencies, cities, etc.

what is an ecological fallacy

situation that can occur when a researcher makes an inference about an individual based on aggregate data for a group such as country/state level data

what is an individualistic fallacy/reductionism

when properties of individuals are used to make an inference about the groups to which they belong

what is data

• raw/minimally processed observations used to perform original analysis

• Ex: survey responses, interview transcripts, administrative records

what are statistics

• summaries or interpretations of data

• Ex: averages, percentages, rates, indices, tables