1. Example: Theories in Public Policy Process

2. Modeling Public Policy Competing Theories of the Policy Process
What are Models?
Models are based on theory.
A theory is a set of logically related set of statements, including some law like generalizations, that are empirically testable.

3. How do we know if models or theories are useful or helpful?
Order and simplify reality
Models help identify what is significant.
Models should be congruent with reality.
Models should provide meaningful communication.
Models should suggest explanations.
Models should direct inquiry and research.

4. where should we look when studying policy
where should we look when studying policy? Theories and models help us answer this question
Day to day decisionmaking
Statutory language
Policy outcomes/effects
Individuals
Institutions
Groups
Elite

6. (neo)Institutional
Rationalism
Incrementalism
Punctuated Equalibrium
Group/Pluralism
Elite
Public Choice
Game theory
Systems theory
Stages Approach

7. Schutt Examples
Functionalism
Conflict Theory
Rational Choice
Symbolic Interaction

8. What is your research philosophy?
What is the difference between Positivism and Post-Positivism?

9. The Assumptions

10. Descriptive: Central Tendency
Mode - The most frequent observation. Usually used with nominal data to describe data. Limitation - limited information - could be multi-modal. Cannot be arithmetically manipulated
Median - the middle observation. Usually used with ordinal level data. Relatively stable. Limitations - must have ordinal data or higher. Cannot be arithmetically manipulated
Mean - Most widely used measure in statistics (i.e., most statistical tests are built around the mean). Can be arithmetically manipulated (calculated). Limitations - must have either interval or ration data, sensitive to outliers
Formula: ∑x / n

11. Measures of Variability or Dispersion
Range - high and lows.
Limitations: Based on only two extreme observations
Interquartile range - measures variablility based on percentiles.
Q3(75th percentile) -Q1 (25th percentile)
Limitations: Leaves our many observations
Mean Deviation – the average of the absolute deviations.
∑|x-µ| / n
Limitations: Less sensitive to deviations in the distribution
Variance - Based on distances from the mean (X - mean).
Takes the square of each deviation from the average and then
averages the squares.
∑(x-µ)2 / n
Standard Deviation - the square root of the variance

12. Why Do We Want a Measure of Variation?
Which is the Better Measure of Variation?
Why do we Square the difference from the mean?
Why do we take the square root of the Variance?
How do we interpret the Standard Deviation

13. Variance Formula