POL 100 Lecture Notes - Lecture 3: Nomothetic, Level Of Measurement, Longitudinal Study
14 May 2018
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Monday, January 22, 2018
Research Methods – Lecture Notes
o Avenues for Inquiry
o Formulating research questions
o Methods for arriving at what we know.
o Explanations: Modes of Causal Reasoning
o Idiographic: Detailed understanding of factors that contribute to a particular
phenomenon.
o Example: If your bike was stolen. Retracing how it happened and to
avoid it happening again.
o Nomothetic: Explain a number of similar phenomena or situations.
o Example: Other people who also had their bike stolen from secluded
areas.
o Reasoning: Logical Models
o Inductive: Moving from specific to general.
o Example: You’re a probation officer and you notice a number of your
clients have not reconvicted. So, you gather data and conclude that the
clients have strong family support.
o Example: Sherlock Holmes or House method.
o Deductive: Moving from general to specific.
o Types of Data
o Quantitative: Numerical data.
o Example: Number of students in a classroom, the number of hours you
study a week, crime rate, etc.
o Qualitative: Non-numerical data (difficult to analyze).
o Example: Crime type, the reason you chose criminology as your major,
etc.
o Causality and Validity
o Causation in the Social Sciences
o X → Y
o Criteria for Causality
o Idiographic Explanations:
o Credible and believable
o Other potential explanations eliminated.
o Nomothetic Explanations:
o Variable must vary together.
o Example: Covariation. Relationship between delinquency and hours
playing violent video games.
o Cause must occur before effect.
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Monday, January 22, 2018
o Example: Cause prior to effect. Video games → Delinquency OR
Delinquency → Video games.
o Relationship not due to some other factor.
o Example: No omitted explanations. ? (delinquent friends) → Video
games.
o Note: Must think of any other relationships and count for those variables.
o Necessary and Sufficient Causes
o Necessary Cause: A condition that must be present for the effect to follow.
o Sufficient Cause: A condition that more or less guarantees the effect in
question.
o Settle for partial explanations
o Necessary and sufficient most of the time.
o Validity
o What is Validity?
o Whether statements about cause or measures are correct.
o Difficult to know with absolute certainty.
o Threats to Validity
o Possible sources of false conclusions about cause or measurement.
o “A way you might be wrong”.
o Statistical Conclusion Validity
o Is the relationship between variables statistically significant?
o Threats due to:
o Nonsystematic error = random error.
o Small sample size (n) – difficult to detect relationship.
o Internal Validity
o Are relationships causal or sue to the effects of some other variable.
o Threats due to:
o Systematic error
o Spurious relationship.
o Uncontrolled environment.
o External Validity
o Can results be replicated in another population, time, or place?
o Threats due to:
o Non-generalizability
o Specific populations, times, or places.
o Construct Validity
o Are measures reflective of the underlying theory or causal process of interest?
o Threats due to:
o Mismatch between construct and measurement
o Measures too narrow to generalize to theoretical processes.
find more resources at oneclass.com
find more resources at oneclass.com
