1. January 17, 2006Lecture 1aSlide 1 BUSH 623: Getting Beyond Fear and Loathing of Statistics Lecture 1 Spring, 2006

2. January 17, 2006Lecture 1aSlide 2 Don’t Panic Motivation: this course is about the connection between theoretical claims and empirical data What we’ll cover (after a very brief review): –Part 1: bi-variate regression –Part 2: multiviariate regression –Part 3: logit analysis and factor analysis

3. January 17, 2006Lecture 1aSlide 3 The place of statistical analysis Programs, policies, legislation typically consist of sets of normative claims and a (sketchy?) theory about how to achieve objectives –Policies typically attempt to map a set of beliefs and empirical claims into society, the economy, international relations. (E.g., welfare reform) Policy analysts need to be able to identify the values served, distill the theory, and evaluate its empirical claims.

4. January 17, 2006Lecture 1aSlide 4 The place of statistical analysis Ingredients of strong empirical research –Theory  claims for policy (and counter-claims) –Hypotheses  measurement  analysis –Findings  Back to theory… –Implications for policy Characterizing data –Data Quality: Valid? Reliable? Relevant? Appropriate model design and execution –Are statistical models appropriate to test hypotheses? –Are models appropriately specified? –Do data conform to statistical assumptions?

5. January 17, 2006Lecture 1aSlide 5 How to survive this class Use the webpage –http://www.tamu.edu/classes/bush/hjsmith/courses/bush632.html Lectures and book: as close as possible Readings: Read ‘em or weep. Questions: Bring ‘em to class, lab, office hours –Or send via email, and (if appropriate) and I will post answers Stata: Use it a lot –“In-class lab” examples and exercises –Download exercises and data in advance –The place of exercises in Bush 632 Nothing late; don’t miss class…

6. January 17, 2006Lecture 1aSlide 6 Class Exams Three Take-home Exams –Usually 4 days to complete –Characteristics and Grading Criteria Connection to theory Clear hypotheses Appropriate statistical analyses Clear and succinct explanations Class data will be provided National Security surveys US/European Scientist dataset

7. January 17, 2006Lecture 1aSlide 7 A Brief Refresher on Functions and Sampling Statistical models involve relationships –Relationships imply functions E.g.: Coffee consumption and productivity Functions are ubiquitous (or chaos prevails) –Most general expression: Y f (X 1, X 2, … X n, e)

8. January 17, 2006Lecture 1aSlide 8 Linear Functions

9. January 17, 2006Lecture 1aSlide 9 Non-Linear Functions

10. January 17, 2006Lecture 1aSlide 10 More Non-Linear Functions

11. January 17, 2006Lecture 1aSlide 11 Functions in Policy Welfare and work incentives –Employment = f(welfare programs, …) Pretty complex Nuclear weapons proliferation –Decision to develop nucs = f(perceived threat, incentives, sanctions, …) Educational Attainment –Test Scores = f(class size, institutional incentives, …) Successful Program Implementation –Implementation = f(clarity, public support, complexity…)

12. January 17, 2006Lecture 1aSlide 12 Reliance on samples is also ubiquitous “Knowing” a person: we sample “Knowing” places: we sample Samples are necessary to identify functions –Samples must cover relevant variables, variable ranges, contexts, etc. Strategies for sampling –Soup and temperature: stir it –Stratify sample: observations in appropriate “cells” –Randomization

13. January 17, 2006Lecture 1aSlide 13 BREAK Review National Security 2005 survey questions and responses Get them here from the homepage homepage Look at distributions of beliefs; policy preferences Hypothesize about factors influencing public support (as functions) for: Aggressive international response to terror strikes in the US Tough (and possibly intrusive) domestic policies to intercept terrorists in the US